Big Data and Analytics Training

Online Instructor-led (2 days)

Online Self-paced (16 hours)

Hadoop Big Data Certification Training Course Outline

Module 1: Understanding Hadoop

  • What is Web Hadoop?
  • Why is Hadoop Important?
  • Hadoop Architecture
  • Challenges of Using Hadoop

Module 2: Processing Distributed Data

  • HDFS
  • MapReduce
    • Architecture
    • Processing Data

Module 3: Introduction to Data Storage and Processing

  • Overview
  • Projects for Structured Data Storage and Processing

Module 4: Defining Hadoop Cluster Requirements

  • Hadoop Cluster
  • Advantages 
  • Hadoop Cluster Architecture 
  • Best Practices for Building Hadoop Cluster

Module 5: Configuring a Cluster

  • Types of Configuration Files Drive Hadoop Configuration
  • Code Example  

Module 6: Maximising HDFS Robustness

  • Three Types of Failures in HDFS
  • Data Disk Failure, Heartbeats, and Re-Replication
  • Cluster Rebalancing
  • Data Integrity
  • Metadata Disk Failure
  • Snapshots

Module 7: Managing Resources and Cluster Health

  • Managing Resources
  • Managing HDFS Cluster
  • Secondary NameNode Configuration
  • MapReduce Cluster Management 

Module 8: Maintaining a Cluster

  • FileSystem Checks 
  • HDFS Balancer Utility 
  • Add New Nodes to Cluster
  • Decommissioning a Node from Cluster
  • Datanode Volume Failures
  • Database Backups
  • HDFS Metadata Backup
  • Purging Older Log Files

Module 9: Extending Hadoop and Implementing Data Ingress

  • Extending Hadoop Towards Data Lake

Module 10: Extending Hadoop and Implementing Data Ingress

  • Hadoop Built-in Ingress and Egress Tools  

Module 11: Planning for Backup, Recovery, and Security

  • Introduction to Backup and Recovery
  • Goals and Objectives

Module 12: Introduction to Big Data

  • What is Big Data? 
  • Three V’s
  • Sources of Big Data  

Module 13: Storing Big Data

  • Introduction to Big Data Storage
  • Key Requirements of Big Data Storage
  • Big Data Storage Architectures

Module 14: Processing Big Data

  • Introduction to Data Processing
  • Big Data Processing Frameworks 
  • What is Traditional Approach?
  • MapReduce
  • Hadoop and Big Data
  • Distributed Storage System
  • YARN
  • Hadoop 1.0/Hadoop 2.0
  • Advantages of Hadoop
  • Hadoop Ecosystem
  • Hortonworks Data Platform

Module 15: Tools and Techniques to Analyse Big Data

  • Apache Hadoop
  • Microsoft HDInsight
  • NoSQL
  • Hive
  • Sqoop
  • PolyBase
  • Big Data in Excel
  • Presto

Module 16: Developing a Big Data Strategy

  • Steps to Develop a Big Data Strategy 
    • Understanding Business Objectives
    • Have a Clear Strategy for Hadoop
    • Build a Data-Driven Culture
    • Choose the Right Platform
    • Start Small

Module 17: Implementing Big Data Solution

  • Steps for Implementing a Big Data Solution
    • Collect and Load Data
    • Process, Query, Transform Data
    • Consume and Visualise Data
    • Build End-To-End Solutions

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Who should attend this Hadoop Big Data Certification Course? 

This Hadoop Big Data Certification Course is suitable for a wide range of individuals who are interested in mastering the concepts and techniques related to Hadoop and Big Data. This course can be beneficial for a wide range of professionals, including:

  • Data Professionals
  • Software Developers
  • Database Administrators
  • System Administrators
  • IT Professionals
  • Business Analysts
  • Project Managers

Prerequisites of the Hadoop Big Data Certification Course

There are no formal prerequisites for this Hadoop Big Data Course.

Hadoop Big Data Certification Training Course Overview

Big Data and Analytics Training has emerged as a critical domain. The Hadoop Big Data Certification Training introduces delegates to the world of Big Data and its relevance in modern business and technology landscapes. With data becoming the lifeblood of organisations, understanding and harnessing Big Data and Analytics is paramount.

Proficiency in Big Data and Analytics Courses is essential for professionals across various domains, including IT, Business, and Data Analysis. Mastering Big Data Analytics Courses can open doors to lucrative career opportunities and allow individuals to harness the power of data to make informed decisions.

This intensive 2-day Big Data Analytics Course empowers delegates with the knowledge and practical skills necessary to navigate the complex landscape of Big Data. Through hands-on experience and expert guidance, delegates will gain the competence to process, analyse, and extract valuable insights from vast data sets.

Course Objectives:

  • To understand the fundamentals of Big Data and Analytics
  • To employ Hadoop technology to manage and process large datasets
  • To perform data analysis and gain insights from Big Data
  • To explore real-world use cases and applications of Big Data Analytics
  • To master the art of data visualisation for effective communication
  • To develop practical problem-solving skills in Big Data scenarios

After completing the Hadoop Big Data Training Course, delegates will receive a certification in Hadoop Big Data Analytics, validating their expertise and enhancing their career prospects in the competitive world of Big Data and Analytics. This certification is a testament to their proficiency in handling and interpreting Big Data, making them valuable assets for the delegate's future.

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What’s included in this Hadoop Big Data Certification Course? 

  • World-Class Training Sessions from Experienced Instructors    
  • Hadoop Big Data Certificate 
  • Digital Delegate Pack

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Online Instructor-led (1 days)

Online Self-paced (8 hours)

Hadoop Administration Training Course Outline

Module 1: Fundamentals of Hadoop

  • Apache Hadoop
  • Why Use Hadoop?

Module 2: Hadoop Ecosystem

  • Overview
  • HDFS
  • MapReduce
  • YARN
  • Common
  • Spark
  • Hive
  • Pig
  • HBase
  • Oozie
  • Sqoop

Module 3: Startup and Admin Commands

  • Startup Commands
  • Admin Commands

Module 4: Commissioning and Decommissioning Nodes

  • Commissioning Nodes
  • Decommissioning Nodes

Module 5: Configuring a Cluster

  • Overview
  • Different Types of Configuration Files Drive Hadoop Configuration
  • Configuration Specification From a core-site.xml File
  • Configuration Specification From a mapred-site.xml File

Module 6: Maintaining a Cluster

  • FileSystem Checks
  • HDFS Balancer Utility
  • Add New Nodes to the Cluster
  • Datanode Volume Failures
  • Database Backups
  • HDFS Metadata Backup
  • Purging Older Log Files

Module 7: Monitoring and Troubleshooting Clusters

  • Managing Resources
  • Managing HDFS Cluster
  • Secondary NameNode Configuration
  • MapReduce Cluster Management

Module 8: Handling Corrupt and Missing Blocks

  • Use Hadoops’s fsck Filesystem Checking Utility
  • Find Out which Files have Corrupt Blocks
  • Deal with the Corrupt Files

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Who should attend this Hadoop Administration Training Course? 

This Hadoop Administration Course is suitable for individuals who aim to develop expertise in managing Hadoop clusters and the associated ecosystem components. This course can be beneficial for a wide range of professionals, including:

  • System Administrators
  • IT Professionals
  • Database Administrators
  • Network Engineers
  • Software Engineers
  • Data Engineers
  • Technical Managers

Prerequisites of the Hadoop Administration Training Course

There are no formal prerequisites for this Hadoop Administration Training Course. However, a basic understanding of Hadoop and a prior knowledge of large data fields would be beneficial for the delegates.

 

Hadoop Administration Training Course Overview

The Hadoop Administration Training Course stands as a cornerstone for professionals seeking to harness the power of large-scale data management and processing. The organisations rely heavily on Big Data and Analytics, so mastering Hadoop Administration is paramount. This course equips individuals with the knowledge and skills needed to manage and optimise Hadoop clusters efficiently, ensuring the seamless flow of data.

Proficiency in Hadoop Administration is of utmost importance for professionals engaged in the management of Big Data and Analytics. Data Engineers, System Administrators, and IT professionals responsible for maintaining and scaling data infrastructure should aim to master this subject. Hadoop Administration skills enable them to configure, monitor, and troubleshoot Hadoop clusters, ensuring data availability, reliability, and performance.

This 1-day training empowers delegates with practical insights and hands-on experience in Hadoop Administration. Delegates will learn essential concepts, best practices, and tools for efficiently managing Hadoop clusters, from installation and configuration to security and performance optimisation. The course combines theory and practical knowledge, ensuring that delegates are well-prepared to tackle the challenges of the Hadoop Administration.

Course Objectives:

  • To understand the fundamentals of Hadoop and its role in Big Data and Analytics
  • To learn cluster installation, configuration, and maintenance techniques
  • To implement robust security measures to safeguard data integrity
  • To optimise Hadoop cluster performance for efficient data processing
  • To acquire hands-on experience with Hadoop ecosystem components
  • To develop best practices for data management and storage
  • To master the art of scaling Hadoop clusters to meet evolving business needs

After completing this Big Data Analytics Training, delegates will receive a prestigious certification recognised within the realm of Big Data and Analytics. This certification validates their expertise in Hadoop Administration, making them valuable assets to organisations in need of efficient data management.

 

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What’s included in this Hadoop Administration Training Course? 

  • World-Class Training Sessions from Experienced Instructors    
  • Hadoop Administration Certificate 
  • Digital Delegate Pack

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Online Instructor-led (1 days)

Online Self-paced (8 hours)

Big Data Architecture Training Course Outline

Module 1: Introduction to Hadoop Development Framework

  • What is Hadoop?
  • Apache Hadoop Framework
  • Hadoop Clusters

Module 2: Real-Time Processing and Batch Processing

  • Real-Time Processing
  • Batch Processing

Module 3: Data Formats and Data Lifecycle

  • What is Big Data?
  • Structure and Unstructured Data
  • Understanding Fundamentals of Big Data

Module 4: Data Model Creation

  • What is Data Model Creation?
  • Benefits of Creating a Structured Repository of Data
  • Modelling Methodologies
  • Partitioning
  • Metadata

Module 5: Database Interface

  • What is Database Interface?
  • Features Database Interface
  • Components of Hue
  • Apache Hive

Module 6: Scaling

  • Steps to Successfully Scaling Big Data

Module 7: Security and Privacy

  • Security Fabric
  • What are the Risks Associated with Big Data Technologies?
  • Principles of Data Privacy

Module 8: Hadoop Clusters

  • What are Hadoop Clusters?
  • Benefits of Building Clusters
  • Disadvantages of Hadoop Clusters
  • Start and Stop Hadoop Cluster

Module 9: Selecting Right Technology

  • Analytic Approach and Data Accuracy
  • Features and Tracking Types
  • Integration and Connectivity
  • Customer Service and Support 
  • Data Storage Options Available
  • Legal Compliance
  • Reliability of the Software and the Supplier
  • Cost
  • Ownership of Data and Customisation Available to the User

Module 10: Big Data and Hadoop Administration

  • Hadoop Administrator(s)
  • Performance Tuning

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Who should attend this Big Data Architecture Training Course? 

This Big Data Architecture Course is designed for professionals and individuals seeking to enhance their understanding and expertise in the field of Big Data architecture. This course can be beneficial for a wide range of professionals, including:

  • Data Architects
  • Data Engineers
  • Database Administrators
  • IT Managers
  • Software Developers
  • Data Scientists
  • Business Analysts

Prerequisites of the Big Data Architecture Training Course

There are no formal prerequisites for this Big Data Architecture Training Course. However, prior knowledge of Database Management Systems and technologies would be beneficial for delegates.

 

Big Data Architecture Training Course Overview

The Big Data Architecture Training is a critical introduction to the world of Big Data and Analytics. In today's data-driven landscape, understanding the intricacies of these fields is paramount. The Big Data Architecture Training offers a comprehensive dive into the world of Big Data and Analytics, providing participants with the knowledge and practical insights needed to excel in the data-driven world.

Proficiency in this training is crucial for anyone seeking to stay competitive. This course is designed for professionals in various fields, including IT, marketing, finance, and more. It equips them with the skills to harness the power of data and make informed decisions, enhancing their career prospects.

This intensive 1-day Big Data and Analytics Course on Big Data Architecture and Analytics empowers delegates with the knowledge and practical insights needed to excel in the data-driven world. Delegates will gain a strong understanding of data processing, storage, and analysis techniques, enabling them to drive business success through data-driven strategies.

Course Objectives:

  • To understand the fundamentals of Big Data and Analytics
  • To explore various Big Data technologies and tools
  • To learn data storage and processing techniques
  • To discover best practices for data security and governance
  • To apply Big Data concepts to real-world scenarios
  • To prepare to tackle Big Data challenges in your profession

After completing this training, delegates will receive a certification attesting to their expertise in Big Data and Analytics. This valuable certification opens doors to a world of career opportunities, allowing professionals to showcase their proficiency in Big Data Analytics Courses and take a leap forward in their career journey.

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What’s included in this Big Data Architecture Training Course? 

  • World-Class Training Sessions from Experienced Instructors    
  • Big Data Architecture Certificate 
  • Digital Delegate Pack

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Online Instructor-led (2 days)

Online Self-paced (16 hours)

Big Data and Hadoop Solutions Architect​ Training Course Outline

Module 1: Getting Started with Big Data and Hadoop

  • Apache Hadoop Ecosystem
  • Big Data and its Challenges
  • What is Big Data?
  • Facebook, Twitter, and Instagram
  • Types of Data
  • Data Volume is Growing Exponentially
  • Hidden Treasure
  • Characteristics of Big Data
    • Scale (Volume)
    • Complexity (Varity)
    • Complexity (Velocity)
  • Big Data
    • 3V’s
    • Some Make it 4V’s
    • Transactions, Interactions, Observations
    • Some Make it 4V’s – Characteristics of Big Data 4V’s
    • Some Make it 4V’s – The V’s of Big Data
    • Harnessing
    • Who’s Generating Big Data?
    • Model has Changed
    • What’s Driving Big Data?
    • Types of Big Data
    • Value of Big Data Analytics

Module 2: What Technology do we have for Big Data?

  • Big Data Technology
  • Big Data Architecture
  • Big Data Design
  • Big Data Usage Sector
  • Big Data: Sample Usage – Customer Sentiment
  • Technology Trends
  • Industries Who Use Big Data?
  • Case Study

Module 3: Apache Hadoop

  • What is Apache Hadoop?
  • Why Use Hadoop?
  • Hadoop and its Characteristics

Module 4: Hadoop Core Components

  • Hadoop Ecosystem
  • Hadoop Services
  • Different Hadoop Methods
  • Hadoop Deployment Modes
  • Motivations for Hadoop
  • Blocks
  • Computer Racks and Block Replication

Module 5: Processing Distributed Data

  • What is HDFS?
  • Hadoop Distributed File System
  • Why DFS?
  • Data Replication
  • Revisit Hadoop Components
  • What is HSFS?
  • Goals of HDFS
  • Features of HDFS
  • Design of HDFS
  • Areas Where HDFS is not a Good Fit Today
  • Abstracting Blocks in HDFS
  • Benefits of Abstracting Blocks in HDFS
  • HDFS Components
  • Main Components of HDFS
  • Secondary NameNode
  • NameNode MetaData
  • Distributed File System
  • Functions of NameNode
  • DataNodes
  • Block Placement

Module 6: Jobs Tracker and Task Tracker

  • Hadoop Distributed File System Architecture
  • Anatomy of File Write and File Read
  • Job Tracker
  • HDFS Creates a New File
  • HDFS
    • Rack Awareness
    • Terminal Commands
    • Running the Teragen Examples
    • Checking the Output
  • Deployment Modes
  • MAPRED-SITE.XML

Module 7: Anatomy of a Cluster

  • Typical Architecture of Hadoop
  • Hadoop Cluster Architecture
  • Core Components of Hadoop Cluster
  • Typical Workflow in HDFS
  • Hadoop Limitations
  • Next-Generation Data Architecture
  • Case Study

Module 8: NoSQL

  • What is NoSQL?  
  • NoSQL Vs RDBMS
  • ACID Vs BASE
  • Single CPU RDBMS
  • NoSQL Data Architecture
  • Key-Value Stores
  • Data Model – Column Families

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Who should attend this Big Data and Hadoop Solutions Architect Course? 

The Big Data and Hadoop Solutions Architect Course is designed for individuals who are seeking to enhance their expertise in the field of Big Data and Hadoop, with a focus on Solutions Architecture. This Big Data and Analytics Course can be beneficial for a wide range of professionals. Including:

  • Data Architects
  • Big Data Engineers
  • Data Scientists
  • Database Administrators
  • IT Managers
  • Software Architects
  • System Administrators

Prerequisites of the Big Data and Hadoop Solutions Architect Course

There are no formal prerequisites for this Big Data and Hadoop Solutions Architect Course. However, some prior knowledge of Hadoop would be beneficial for the delegates.

 

Big Data and Hadoop Solutions Architect Training Course Overview

The Big Data and Hadoop Solutions Architect Course provides essential insights into processing vast datasets. Understanding this training is crucial for professionals aiming to stay ahead in a competitive market where data-driven decisions steer success. This training addresses the heart of modern data challenges, offering a comprehensive understanding of Big Data Analytics Courses.

Proficiency in this course is indispensable for professionals seeking to navigate the complexities of modern data ecosystems. Data scientists, Analysts, and IT Professionals must master this field to leverage the power of data effectively. Learning this training empowers you to harness the full potential of data analytics tools, making you an invaluable asset in any data-driven organisation.

This intensive 1-day training course equips delegates with hands-on experience in Big Data and Analytics. Through practical exercises and real-world scenarios, participants gain proficiency in Big Data and Analytics solutions. By the end of the course, delegates will possess the skills to architect Hadoop solutions, ensuring efficient data processing and analysis.

Course Objectives:

  • To understand the fundamentals of Big Data and Analytics
  • To develop skills in real-time data processing and storage
  • To learn advanced data analytics techniques for actionable insights
  • To explore tools and technologies in the Big Data ecosystem
  • To understand security and data governance in Big Data environments
  • To implement best practices for scalable and efficient data solutions

After completing this Big Data and Analytics Course, delegates will receive a prestigious certification. This certification validates your expertise in these courses, making you a recognised authority in the field.

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What’s included in this Big Data and Hadoop Solutions Architect Course? 

  • World-Class Training Sessions from Experienced Instructors    
  • Big Data and Hadoop Solutions Architect Certificate 
  • Digital Delegate Pack 

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Data Science Analytics Course Outline

Module 1: Introduction to Data Science

  • What is Data Science?
  • Types of Data
  • Data Science Pipeline

Module 2: Understanding Data Wrangling

  • Data Wrangling Workflow
  • Data Acquisition
  • Five Steps of the Data Collection Process
  • Data Enriching
  • Data Cleansing

Module 3: Data Analysis

  • Data Analysis within Business
  • Confirmatory Data Analysis
  • Exploratory Data Analysis
  • Data Analysis Files

Module 4: Data Mining

  • Introduction to Data Mining
    • Common Classes of Tasks Under Data Mining
  • Regression Analysis

Module 5: Understanding Data Visualisation

  • Introduction to Data Visualisation
    • Six Principles of Data Visualisation
    • Elements of Data Visualisation
  • Psychology of Charts

Module 6: Data Manipulation

  • Data Manipulation Overview
  • Types of Structuring Involved in Data Manipulation
    • Intrarecord Structuring
    • Interrecord Structuring

Module 7: Working with Large Amounts of Data

  • What is Big Data?
    • Different Devices and Applications
  • Fundamentals of Big Data
    • 3 V’s
    • Sources of Big Data
  • Data Tools
  • Structure
  • Sampling
    • Methods of Sampling
  • Chunking Principles
    • How Big Should Data Chunks Be?

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Who should attend this Data Science Analytics Course? 

This Data Science Analytics Course is suitable for a wide range of individuals looking to enhance their skills and knowledge in the field of Data Science and Analytics. This Big Data and Analytics Course can be beneficial for a wide range of professionals, including:

  • Data Analysts
  • Business Analysts
  • Data Scientists
  • IT Professionals
  • Managers
  • Entrepreneurs
  • Financial Analysts

Prerequisites of the Data Science Analytics Course

There are no formal prerequisites for this Data Science Analytics Course.

 

Data Science Analytics Course Overview

Introduction to the Data Science Analytics Course reveals the significance of harnessing the power of Big Data and Analytics. In an era defined by information, businesses and professionals who can derive insights from vast datasets gain a competitive edge, making Big Data Analytics Courses a pivotal field of study.

Proficiency in Big Data Analytics Courses is vital for professionals across various domains, including Business, Finance, Healthcare, and Technology. It empowers them to extract valuable information from vast datasets, enhancing decision-making and driving organisational success. Anyone aspiring to excel in their respective fields should aim to acquire proficiency in this subject.

This intensive 1-day training provides a comprehensive introduction to Big Data and Analytics, equipping delegates with the fundamental skills needed for data analysis. Through practical applications and real-world case studies, participants will gain hands-on experience in data handling, interpretation, and visualisation.

Course Objectives:

  • To understand the fundamentals of data science and analytics
  • To learn data collection, cleaning, and preparation techniques
  • To develop proficiency in data visualisation and interpretation
  • To gain insights into machine learning and predictive analytics
  • To explore the impact of Big Data on business strategies
  • To enhance decision-making through data-driven insights

After completing this course, delegates will receive a certification in Big Data Analytics Courses, validating their expertise in data science and analytics. This certification serves as a valuable asset, opening doors to new career opportunities and enhancing professional growth.

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What’s included in this Data Science Analytics Course? 

  • World-Class Training Sessions from Experienced Instructors    
  • Data Science Analytics Certificate 
  • Digital Delegate Pack

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Data Analytics with R Course Outline

Module 1: Overview of Data Analysis

  • Introduction to Data Analysis
  • Phases of Data Analytics Lifecycle
  • Types of Data Analysis
  • Data Analysis Characteristics
  • Applications of Data Analysis

Module 2: Business Intelligence and Analytics

  • Business Intelligence
  • BI Lifecycle
  • BI Intelligence and Analytics

Module 3: R Programming Language

  • R Programming Language
  • Data Types
  • Simple Operations
  • Executing Commands
  • Vectors
  • List
  • Matrix
  • Array in R
  • Data Manipulation in R
  • Control Structures in R
  • Descriptive Statistics

Module 4: Importing Data

  • What is Importing Data?
  • Process of Importing Data in R

Module 5: Machine Learning

  • Introduction to Machine Learning 
  • Machine Learning Process
  • Important Machine Learning Tools for R
  • Regression Analysis
  • Linear Regression
  • Logistic Regression
  • Decision Tree 

 

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Who should attend this Data Analytics with R Course?  

The Data Analytics with R Course is designed for individuals seeking to harness the power of data to make informed decisions. This course offers insights and tools to propel your analytical capabilities. This course can be beneficial for a wide range of professionals, including:

  • Data Analysts
  • Statisticians
  • Business Analysts
  • Financial Analysts
  • Marketing Analysts
  • Researchers
  • Healthcare Data Professionals
  • IT and Software Engineers

Prerequisites of the Data Analytics with R Course 

There are no formal prerequisites for this Data Analytics with R Course.

Data Analytics with R Course Overview

Data Analytics with R Course is a crucial component of Big Data and Analytics Training. In today's data-driven world, the power of R for data analysis is paramount. R, a programming language and environment widely used for statistical analysis and data visualisation, holds the key to uncovering actionable insights from vast datasets. Its relevance is evident in its ability to aid professionals in making informed decisions based on data-driven findings.

Proficiency in R is the ability to harness R's capabilities, enabling them to extract meaningful patterns from complex datasets, aiding in informed decision-making. For instance, data scientists proficient in R can explore trends and uncover hidden insights in various industries, making it a critical skill for career advancement.

The 1-day course offered by the Knowledge Academy is designed to empower delegates with the knowledge and practical skills they need for data analytics with R. Through hands-on experience in data manipulation, statistical analysis, and data visualisation using R, participants will gain a deep understanding of the subject. The course emphasizes real-world applications, ensuring that delegates are well-equipped to tackle data-related challenges effectively.

Course Objectives:

  • To gain expertise in exploratory data analysis and visualisation techniques
  • To acquire knowledge of advanced statistical methods for data interpretation
  • To understand machine learning algorithms and their application in data analytics
  • To learn to create interactive dashboards for data presentation
  • To implement real-time analytics solutions using R and Big Data technologies
  • To apply ethical considerations and best practices in data analytics projects

After completing this Big Data and Analytics Course, you will receive a certification, validating your proficiency in R for data analytics. This certification serves as a tangible proof of your skills and enhances your career prospects.

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What’s included in this Data Analytics with R Course? 

  • World-Class Training Sessions from Experienced Instructors    
  • Data Analytics with R Certificate 
  • Digital Delegate Pack

 

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Big Data Analysis Course Outline

Module 1: Understanding the Fundamentals of Big Data

  • What is Big Data?
  • Understanding the Fundamentals of Big Data
    • Sources of Big Data
    • Big Data Analysis Lifecycle

Module 2: Planning a Big Data Approach to Business

  • Bottom – Up and Top Down Planning
  • Technologies
  • Considering Use Case
  • Thinking Long Term
  • Steps of Planning

Module 3: Implementing a Big Data Approach to Business

  • Recognising Business Challenges
  • Finding Appropriate Data Sources
  • Involving The Business
  • Choosing What to Use

Module 4: Storing Unstructured Information

  • Storing Unstructured Information
    • Apache Hadoop
    • Microsoft HDInsight
    • Hive
    • PolyBase
    • Sqoop
    • Presto
    • Microsoft Excel
    • No SQL

Module 5: Managing Unstructured Information

  • Challenges of Unstructured Data
  • Deciding on a Data Source
  • Preparing for storage
  • Choosing Storage Solutions

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Who should attend this Big Data Analysis Course? 

The Big Data Analysis Course is designed for individuals who want to acquire a comprehensive understanding of handling and interpreting large volumes of data effectively. This Big Data and Analytics Training Course can be beneficial for a wide range of professionals, including:

  • Data Analysts
  • Data Scientists
  • Business Analysts
  • IT Professionals
  • Managers and Executives
  • Entrepreneurs
  • Software Engineers

Prerequisites of the Big Data Analysis Course

There are no formal prerequisites for this Big Data Analysis Course.

 

 

Big Data Analysis Course Overview

Big Data and Analytics Training is a field that has become pivotal in today's world. This course has revolutionised decision-making processes across industries, making it an indispensable domain. With data-driven insights at the forefront of modern business strategies, mastering Big Data Analytics Courses has never been more relevant.

Proficiency in Big Data Analysis Courses is crucial for professionals across various sectors, including IT, Finance, Marketing, and Healthcare. Whether you are a Data Scientist, a Business Analyst, or an aspiring Entrepreneur, mastering Big Data and Analytics is essential. The ability to extract valuable insights from vast datasets is a skill that can propel your career to new heights.

This intensive 1-day Big Data and Analytics Training will empower delegates with the knowledge and tools required to harness the power of data. From understanding data sources to performing in-depth analyses, this course will equip delegates with practical skills. With hands-on exercises and real-world case studies, delegates will leave with a comprehensive understanding.

Course Objectives:

  • To learn data preprocessing techniques for large datasets
  • To master statistical analysis methods for drawing meaningful insights
  • To acquire skills in predictive modelling and machine learning algorithms
  • To explore data visualisation tools for effective communication of findings
  • To enhance problem-solving abilities through hands-on exercises
  • To develop expertise in handling unstructured data sources like social media and sensor data

After completing this course delegates will receive a Big Data and Analytics Certification, validating their knowledge and opening doors to a wide range of opportunities. This certification will serve as a testament to their proficiency and commitment to mastering the Big Data and Analytics domain.

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What’s included in this Big Data Analysis Course? 

  • World-Class Training Sessions from Experienced Instructors    
  • Big Data Analysis Certificate 
  • Digital Delegate Pack

Show moredown

Online Instructor-led (2 days)

Online Self-paced (16 hours)

Apache Kafka Training Course Outline

Module 1: Introduction to Big Data

  • Big Data
  • Five V’s
  • Sources of Big Data

Module 2: Overview of Kafka

  • Publish/Subscribe Messaging
  • Enter Kafka
  • Data Ecosystem

Module 3: Installing Kafka

  • Installing Java and Zookeeper
  • Hardware Selection
  • Kafka Clusters

Module 4: Kafka Producers

  • Creating a Kafka Producer
  • Sending Message to Kafka
  • Configuring Producers
  • Serializers
  • Partitions

Module 5: Kafka Consumers

  • Create Kafka Consumer
  • Poll Loop
  • Configuring Consumers
  • Commits and Offsets
  • Rebalance Listeners
  • Deserializers

Module 6: Kafka Internals

  • Cluster Membership
  • Controller
  • Replication
  • Request Processing

Module 7: Reliable Data Delivery

  • Reliability Guarantees
  • Replication
  • Broker Configuration
  • Using Producers and Consumers in a Reliable System

Module 8: Building Data Pipelines

  • Considerations When Building Data Pipelines
  • Kafka Connect
  • Running Connect
  • Connectors and Tasks
  • Workers
  • Alternatives to Kafka Connect

Module 9: Cross-Cluster Data Mirroring

  • Use Cases of Cross-Cluster Mirroring
  • Multicluster Architectures
  • Apache Kafka’s MirrorMaker

Module 10: Administering and Monitoring Kafka

  • Overview
  • Topic Operations
  • Consumer Groups
  • Dynamic Configuration Changes
  • Partition Management

Module 11: Stream Processing

  • What is Stream Processing?
  • Stream Processing Concepts
  • Stream-Processing Design Patterns
  • Kafka Streams: Architecture Overview

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Who should attend this Apache Kafka Training Course? 

The Apache Kafka Course is designed for a wide range of professionals seeking to enhance their knowledge and skills in working with Apache Kafka. This Apache Kafka Certification Training can benefit a wide range of professionals, including:

  • Data Analysts
  • Data Engineers
  • Software Developers
  • Database Administrators
  • IT Managers
  • Technical Managers
  • Application Architects

Prerequisites of the Apache Kafka Training Course

There are no formal prerequisites for this Apache Kafka Training Course. However, prior knowledge of Java programming would be beneficial for a smoother learning experience.

Apache Kafka Training Course Overview

Apache Kafka is a real-time distributed event streaming platform and is a vital component of modern data architectures. It enables organisations to process, analyse, and transport data in a scalable, fault-tolerant manner. The significance of Kafka's cannot be overstated. It's the backbone of real-time data processing, making it essential for businesses striving to stay competitive in an ever-evolving landscape.

Proficiency in Apache Kafka is paramount in the age of big data and real-time analytics. Data engineers, developers, and data architects aiming to master Kafka unlock the potential to design robust, scalable, and fault-tolerant systems. Embracing this Apache Kafka Course empowers professionals to navigate the complexities of modern data integration, making them invaluable assets to their organisations.

This intensive 2-day Apache Kafka Training is designed to provide delegates with hands-on experience in Apache Kafka. Delegates will gain practical skills in setting up Kafka clusters, understanding its architecture, and implementing end-to-end data pipelines. They will learn how to optimise Kafka for their specific use cases and troubleshoot common issues, ensuring their organisations can leverage Kafka's full potential effectively.

Course Objectives

  • To understand Kafka fundamentals, including topics, partitions, and replication
  • To master Kafka architecture, exploring producers, consumers, and brokers
  • To implement fault tolerance and high availability in Kafka clusters
  • To delve into advanced topics like Kafka Connect and Kafka Streams
  • To learn best practices for configuration and performance tuning
  • To explore security mechanisms, ensuring data integrity and privacy
  • To design real-time data processing pipelines using Kafka
  • To troubleshoot common issues and optimise Kafka clusters for efficiency

After completing the Apache Kafka Training Course, delegates receive a prestigious certification. These Apache Kafka Courses validate their expertise in Kafka's architecture, administration, and application, making them highly sought-after professionals in the competitive tech industry.

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What’s included in this Apache Kafka Training Course? 

  • World-Class Training Sessions from Experienced Instructors    
  • Apache Kafka Certificate 
  • Digital Delegate Pack 

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Online Instructor-led (2 days)

Online Self-paced (16 hours)

Apache Spark Training Course Outline

Module 1: Introduction to Apache Spark

  • What is Apache Spark?
  • Cluster Design
  • Cluster Management
  • Performance

Module 2: Apache Spark MLlib

  • Environment Configuration
  • Classification with Naive Bayes
  • Clustering with K-Means
  • Artificial Neural Networks (ANN)

Module 3: Apache Spark Streaming

  • Fault Tolerance
  • Apache Kafka
  • TCP Stream
  • Apache Flume

Module 4: Apache Spark SQL

  • SQL Context
  • DataFrames
  • Using SQL
  • User-Defined Functions
  • Using Hive

Module 5: Apache Spark GraphX

  • Environment
  • Neo4j Browser
  • Mazerunner for Neo4j

Module 6: Graph-Based Storage

  • Overview of Titan and TinkerPop
  • Installing Titan
  • Titan with HBase
  • Titan with Cassandra

Module 7: Spark Databricks

  • Installing Databricks
  • Databricks Menus
  • Account and Cluster Management
  • Notebooks and Folders
  • Jobs and Libraries
  • Databricks Tables
  • DbUtils Package

Module 8: Databricks Visualisation

  • Data Visualisation
  • REST Interface
  • Moving Data

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Who should attend this Apache Spark Training Course? 

This Apache Spark Training Course is designed for individuals who want to enhance their skills and knowledge in Big Data processing using Apache Spark. This course can benefit a wide range of professionals, including: 

  • Data Scientists
  • Data Engineers
  • Software Developers
  • Database Professionals
  • Big Data Analysts
  • Technical Managers
  • Business Analysts

Prerequisites of the Apache Spark Training Course

There are no formal prerequisites for this Apache Spark Course. However, prior knowledge of Java programming would be beneficial.

 

Apache Spark Training Course Overview

Apache Spark has emerged as a vital tool for processing and analysing large-scale datasets efficiently. With its widespread use in data engineering and data science, understanding Apache Spark is essential. This course offers a comprehensive exploration of Spark, shedding light on its significance in the modern data landscape enabling professionals to harness its potential for diverse applications.

Proficiency in this course is imperative for professionals across various domains, including data scientists, data engineers, and big data analysts. The ability to work with Spark empowers individuals to handle massive datasets, perform real-time data processing, and derive actionable insights. Mastering Spark is the key to unlocking opportunities and enhancing career prospects in the data and analytics field.

The Knowledge Academy’s 2-day Apache Spark Course equips delegates with the practical skills needed to leverage Apache Spark effectively. During the course, participants will gain hands-on experience in essential Spark components, including Spark SQL, Spark Streaming, and MLlib. They will also learn to build data pipelines, conduct real-time analysis, and optimise Spark applications for enhanced performance.

Course Objectives

  • To understand the fundamental concepts of Spark and its ecosystem
  • To gain proficiency in Spark SQL for querying structured data
  • To learn to process real-time data streams using Spark Streaming
  • To develop machine learning models with Spark's MLlib library
  • To create robust data pipelines for scalable data processing
  • To optimise Spark applications for improved performance
  • To apply Spark in practical projects to solve real-world problems

Upon completing the Apache Spark Course, delegates will gain a comprehensive understanding of distributed data processing, enabling them to tackle big data challenges with efficiency and confidence. Additionally, they will acquire valuable skills in data analytics, Machine Learning, and real-time data processing, making them highly sought-after professionals in the field of data engineering and data science.

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What’s included in this Apache Spark Training Course?

  • World-Class Training Sessions from Experienced Instructors    
  • Apache Spark Certificate 
  • Digital Delegate Pack

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Online Instructor-led (1 days)

Online Self-paced (8 hours)

Apache Storm Training Course Outline

Module 1: Introduction to Apache Storm

  • What is Apache Storm?
  • Apache Storm Vs Hadoop
  • Use-Cases of Apache Storm
  • Apache Storm – Benefits

Module 2: Apache Storm Core Concepts

  • Topology
  • Tasks
  • Workers
  • Stream Grouping

Module 3: Storm-Cluster Architecture

  • Architecture of Apache Storm Cloud
  • Components

Module 4: Apache Storm Workflow

  • Workflow of Apache Storm
  • Modes in a Storm Cluster

Module 5: Distributed Messaging System

  • What is Distributed Messaging System?
  • Thrift Protocol

Module 6: Apache Storm – Installation

  • Step 1: Verifying Java Installation
  • Step 2: ZooKeeper Framework Installation
  • Step 3: Apache Storm Framework Installation

Module 7: Apache Storm Working Example

  • Scenario – Mobile Call Log Analyser
  • Spout Creation
  • Bolt Creation
  • Call log Creator Bolt
  • Call log Counter Bolt
  • Creating Topology
  • Local Cluster
  • Building and Running the Application
  • Non-JVM languages

Module 8: Apache Storm Trident

  • Trident Topology
  • Trident Tuples
  • Trident Spout
  • Trident Operations
  • State Maintenance
  • Distributed RPC
  • When to Use Trident?
  • Working Example of Trident
  • Building and Running the Application

Module 9: Apache Storm in Twitter

  • Twitter
  • Hashtag Reader Bolt
  • Hashtag Counter Bolt
  • Submitting a Topology
  • Building and Running the Application

Module 10: Apache Storm in Yahoo! Finance

  • Spout Creation
  • Bolt Creation
  • Submitting a Topology
  • Building and Running the Application

Module 11: Apache Storm Applications

  • Klout
  • Weather Channel
  • Telecom Industry

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Who should attend this Apache Storm Training Course? 

The Apache Storm Course is designed for individuals who wish to enhance their expertise in real-time data processing and stream processing using the Apache Storm framework. This course can benefit a wide range of professionals, including: 

  • Data Scientists
  • Data Engineers
  • Software Developers
  • Database Administrators
  • IT Professionals
  • Technical Managers
  • System Architects

Prerequisites of the Apache Storm Training Course

There are no formal prerequisites for this Apache Storm Training Course. However, prior knowledge of Java programming would be beneficial.

 

Apache Storm Training Course Overview

In today's data-driven world, Apache Storm stands out as a powerful open-source stream processing framework. This essential tool empowers organisations to efficiently handle massive data streams, providing real-time insights crucial for informed decision-making. In an age where data holds supreme importance, this course is designed to equip individuals with the expertise needed to unlock Apache Storm's potential, positioning them as invaluable assets in industries driven by data.

Proficiency in Apache Storm is indispensable for professionals working in data engineering, data science, and data analytics. It's equally relevant for software developers and architects seeking to build real-time data processing applications as data becomes the lifeblood of businesses. Those who master Storm gain a competitive edge, enabling them to design efficient, real-time data pipelines and derive actionable insights from incoming streams.

This intensive 1-day training empowers delegates with the expertise needed to harness the full potential of Apache Storm. Delegates will gain hands-on experience in setting up Storm clusters, designing topologies, and processing real-time data efficiently. They'll learn best practices and troubleshooting techniques, ensuring they can contribute effectively to real-time data processing projects from day one.

Course Objectives:

  • To understand the core concepts of Apache Storm and its role in real-time data processing
  • To learn how to set up and configure Storm clusters for optimal performance
  • To design and develop Storm topologies for processing real-time data streams
  • To implement data spouts and bolts to ingest and manipulate data within Storm
  • To explore real-world use cases and best practices for Storm-based solutions
  • To ensure fault tolerance and scalability in Storm applications

Upon completing this Apache Storm Training, delegates will gain a deep understanding of stream processing, enabling them to harness real-time data insights for informed decision-making. This expertise will not only enhance their career prospects but also make them valuable contributors in data-driven industries, providing a competitive edge in a rapidly evolving professional landscape.

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What’s included in this Apache Storm Training Course?

  • World-Class Training Sessions from Experienced Instructors    
  • Apache Storm Certificate 
  • Digital Delegate Pack

Show moredown

Online Instructor-led (2 days)

Online Self-paced (16 hours)

Big Data Analytics & Data Science Integration Course Outline

Module 1: Big Data Analytics

  • Big Data Analytics
  • Bigdata
  • State of Practice in Analytics
  • Main Roles for New Big Data Ecosystem

Module 2: Data Analytics Lifecycle

  • Phases of Data Analytics Lifecycle
    • Discovery
    • Data Preparation
    • Model Planning
    • Model Building
    • Communicate Results
    • Operationalise

Module 3: Basic Data Analytic Methods Using R

  • R Programming Language
  • Evolution of R
  • Features of R
  • R Programming Language
  • Exploratory Data Analysis
  • Confirmatory Data Analysis
  • Statistical Methods for Evaluation
  • Regression
  • Classification

Module 4: Introduction to Clustering

  • Applications of Clustering
    • Marketing
    • Retail
    • Medical Science
    • Sociology

Module 5: Association Rules

  • Introduction
  • Apriori Algorithm
  • Applications of Association Rules
  • Validation and Testing

Module 6: Regression

  • Regression Analysis
  • Linear Regression
  • Logistic Regression

Module 7: Classification

  • Decision Tree
  • Decision Tree Example
  • Naïve Bayes

Module 8: Time Series Analysis

  • Introduction
  • Syntax

Module 9: Text Analysis

  • Introduction
  • Term Frequency – Inverse Document Frequency

Module 10: MapReduce and Hadoop

  • Big Data: Types of Big Data
  • Hadoop
  • Hadoop Architecture
  • NoSQL

Module 11: In-Database Analytics

  • In-Database Analytics
  • SQL Essentials
  • Advanced SQL

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Who should attend this Big Data Analytics & Data Science Integration Course? 

The Big Data Analytics & Data Science Integration Course is designed to integrate the principles of Data Science with the tools and technologies needed to deal with Big Data. This course can benefit a wide range of professionals, including: 

  • Data Scientists
  • Data Analysts
  • Software Engineers
  • Managers 
  • IT Professionals
  • Entrepreneurs
  • Business Analysts

Prerequisites of the Big Data Analytics & Data Science Integration Course

There are no formal prerequisites for this Big Data Analytics & Data Science Integration Course.

Big Data Analytics & Data Science Integration Course Overview

The Big Data Analytics & Data Science Integration Course is designed to explore the synergy between big data analytics and data science methodologies, providing a comprehensive understanding of their integration. Participants will delve into the core concepts, tools, and techniques essential for extracting meaningful insights from vast datasets.

Proficiency in big data analytics and data science is paramount for professionals aiming to drive data-driven decision-making within their organisations. Data scientists, analysts, IT professionals, and business strategists should aspire to master this domain. This course is tailored for individuals seeking to elevate their skills in the realm of data analysis and interpretation.

This intensive 1-day training offers delegates a unique opportunity to bridge the gap between big data analytics and data science. Through hands-on workshops, real-world case studies, and interactive sessions, participants will acquire practical skills in data preprocessing, predictive modelling, and data visualisation. By the end of the training, delegates will be proficient in leveraging cutting-edge tools and frameworks, empowering them to extract actionable insights from complex datasets.

Course Objectives:

  • To understand the fundamentals of big data analytics and data science integration
  • To master data preprocessing techniques, including data cleaning and transformation
  • To explore advanced predictive modelling algorithms for accurate data analysis
  • To learn to extract insights from unstructured data using natural language processing
  • To understand the ethical considerations and challenges in big data analytics

Upon completing the Big Data Analytics & Data Science Integration Course, delegates will gain a comprehensive understanding of the synergy between data analytics and data science, allowing them to effectively bridge the gap between these two disciplines. This knowledge will empower them to tackle complex data-related challenges, make data-driven decisions, and excel in their roles in the ever-evolving field of data analysis and science.

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What’s included in this Big Data Analytics & Data Science Integration Course?

  • World-Class Training Sessions from Experienced Instructors    
  • Big Data Analytics & Data Science Integration Certificate 
  • Digital Delegate Pack

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Couchbase Training Course Outline

Module 1: Introduction to Couchbase Server

  • What is Couchbase Server?

Module 2: Installing Couchbase Server

  • Steps to Install Couchbase Server
  • Estimate Cluster Size Requirements
  • Network Ports

Module 3: Couchbase Administration Console Basics

  • Clusters, Buckets, and Servers
  • Create and Edit Data Buckets
  • Couchbase Server Statistics

Module 4: Developing with Couchbase

  • Deployment Options
  • Basic Operations
  • Storing Data
  • Client Interaction with the Cluster

Module 5: Cluster Monitoring

  • Monitoring Nodes and Buckets
  • Monitoring Server Nodes

Module 6: Managing Cluster

  • Adding Node
  • Removing Node
  • Rebalancing
  • Failover with Couchbase
  • Backup and Restore

 

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Who should attend this Couchbase Training Course? 

This Couchbase Training Course is designed for professionals who want to enhance their skills and understanding of Couchbase, a NoSQL database technology. This course can benefit a wide range of professionals, including: 

  • Developers
  • Database Administrators
  • Data Engineers
  • Software Engineers
  • System Architects
  • Technical Leads
  • IT Professionals

Prerequisites of the Couchbase Training Course

There are no formal prerequisites for this Couchbase Training Course.

Couchbase Training Course Overview

Couchbase is a prominent NoSQL database solution that is widely used in contemporary data-driven industries. Couchbase Training is a comprehensive program that empowers individuals with the expertise to leverage Couchbase. This technology is highly pertinent, facilitating real-time data processing, scalability, and flexibility, proving indispensable for developers, administrators, and data experts.

Proficiency in Couchbase is crucial for various professionals, including database administrators, software developers, and data architects. As data volumes continue to surge, mastering Couchbase ensures that these professionals can efficiently manage, develop, and architect solutions that scale seamlessly and deliver exceptional performance.

This 1-day training offers delegates a unique opportunity to delve deep into Couchbase's capabilities. Delegates will gain practical insights into installation, configuration, and performance optimisation. They will learn to design robust data models, ensuring data consistency and reliability. With hands-on exercises, attendees will be able to apply their knowledge immediately, enhancing their problem-solving skills and productivity.

Course Objectives:

  • To learn how to install and configure Couchbase, ensuring a stable operational environment
  • To master data modelling to design efficient and scalable database solutions
  • To develop proficiency in querying and indexing data in Couchbase
  • To explore advanced topics like data replication and cross-data centre deployments
  • To optimise performance for high-throughput applications
  • To gain practical troubleshooting skills for Couchbase-related issues   

Upon completion of the Couchbase Training, delegates will gain a comprehensive understanding of Couchbase's NoSQL database system, enabling them to proficiently manage and leverage this technology in their professional roles. This knowledge will empower them to enhance data storage and retrieval processes, improve application performance, and contribute to the success of data-centric projects.

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What’s included in this Couchbase Training Course? 

  • World-Class Training Sessions from Experienced Instructors    
  • Couchbase Certificate 
  • Digital Delegate Pack

Show moredown

Online Instructor-led (2 days)

Online Self-paced (16 hours)

Data Analysis Training using MS Excel Course Outline

Module 1: Overview of Data Analysis

  • What is Data Analysis?
  • Why Data Analysis?
  • Types of Data Analysis
  • Data Analysis Process

Module 2: Introduction to Data Analysis with MS Excel

  • Introduction to Excel Data Analysis
  • Data Cleaning
  • Data Analysis
  • Data Visualisation

Module 3: Excel Ribbon and Importing Data into Excel

  • Excel Ribbons
  • Importing Data into Excel

Module 4: Work with Range Names

  • Steps to Create Range Name
  • How to Rename Range Name?
  • How to Delete Range Name?
  • Use Name Range in Workbook

Module 5: Introduction to Tables

  • What is a Table?
  • What is the Purpose of Creating a Table?

Module 6: Cleaning Data with Text Functions

  • Removing Unwanted Characters from the Text
  • Steps for Data Cleaning

Module 7: Working with Date Formats and Time Formats

  • Steps to Change Data Format
  • Steps to Change Time Format

Module 8: Conditional Formatting in Excel

  • What is Conditional Formatting and How to Use It?
  • Apply Conditional Formatting on Text

Module 9: Sorting and Filtering Data Columns

  • What is Sorting and Filtering?
  • Sort a Particular Column
  • Applying Sorting on Two Columns
  • Steps to Sort Dates
  • Clear Filter
  • Apply Filter on Text
  • Apply Filter by Cell Icon

Module 10: Subtotals and Quick Analysis

  • Subtotals
  • Steps to Apply Subtotals
  • Quick Analysis
  • Steps to Use Quick Analysis

Module 11: Working with Multiple Sheets

  • Worksheet Tab
  • Viewing Multiple Worksheets at Once
  • Grouping Your Worksheets Together
  • Steps to Rename a Worksheet
  • Steps to Move/Copy a Worksheet
  • Steps to Delete a Worksheet

Module 12: Data Validation

  • What is Data Validation?
  • How to Use Data Validation?
  • Using Data Validation?

Module 13: Data Visualisation

  • What is Data Visualisation?
  • Using Charts in Excel
  • All Charts in Excel

Module 14: Exploring Lookup Functions

  • Lookup Function
  • VLOOKUP and HLOOKUP
  • INDEX Function
  • MATCH Function

Module 15: Pivot Tables

  • PivotTable Overview
  • Creating a PivotTable in MS Excel
  • Recommended PivotTables
  • PivotTable Fields
  • PivotTable Areas
  • Filters and Slicers
  • Summarising Values by Other Calculation
  • Using ANALYSE and DESIGN on the Ribbon

Module 16: What If Analysis

  • What If Analysis
  • What If Analysis with Data Tables
  • What If Analysis with Scenario Manager
  • What If Analysis with Goal Seek

 

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Who should attend this Data Analysis Training using MS Excel Course? 

This Data Analysis Training using MS Excel is suitable for a diverse range of individuals looking to enhance their analytical skills. This Big Data and Analytics can be beneficial for a wide range of professionals, including:

  • Data Analysts
  • Business Analysts
  • Financial Analysts
  • Market Research Analysts
  • Operations Analysts
  • Marketing Analysts
  • Risk Analysts
  • Reporting Analysts
  • Business Intelligence Analysts

Prerequisites of the Data Analysis Training using MS Excel Course

There are no formal prerequisites for this Data Analysis Training using MS Excel Course. However, basic knowledge of MS Excel would be beneficial for the delegates.

Data Analysis Training using MS Excel Course Overview

The Data Analysis Training using MS Excel Course provides a crucial stepping stone into the world of data analysis, empowering delegates to unlock valuable insights from datasets. With the prevalence of data-driven decision-making across various industries, this training is more relevant than ever. As organisations harness the power of data to make informed decisions, individuals must equip themselves with the right skills.

Proficiency in data analysis is paramount for professionals from diverse backgrounds. From Business Analysts to marketing managers and financial planners to healthcare administrators, anyone seeking to harness the potential of data can benefit from mastering this subject. Competence in data analysis becomes essential for career advancement and staying competitive in the job market.

This intensive 1-day Big Data and Analytics Training equips delegates with practical skills to manipulate and analyse data effectively using MS Excel. Delegates will gain the ability to clean and preprocess data, create insightful visualisations, and draw meaningful conclusions from their analysis. The course fosters a hands-on approach, ensuring that delegates leave with actionable skills that can be applied immediately in their professional roles.

Course Objectives:

  • To develop the skills to create informative data visualisations
  • To gain insights into statistical analysis and hypothesis testing
  • To master pivot tables and data modelling for decision support
  • To understand how to make data-driven recommendations
  • To explore real-world case studies and practical applications
  • To enhance problem-solving skills through data analysis challenges

After completing this Big Data and Analytics Course, delegates will receive a certification in Data Analysis Training using MS Excel. This certification not only validates their newly acquired skills but also enhances their professional credibility.

 

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What’s included in this Data Analysis Training using MS Excel Course?

  • World-Class Training Sessions from Experienced Instructors    
  • Data Analysis Training using MS Excel Certificate 
  • Digital Delegate Pack

Show moredown

Online Instructor-led (2 days)

Online Self-paced (16 hours)

Data Integration and Big Data using Talend Course Outline

Module 1: Getting Started with Talend Big Data

  • Talend Unified Platform Presentation
  • Knowing About the Hadoop Ecosystem
  • Prerequisites for Running Examples
  • Downloading Talend Open Studio for Big Data
  • Installing TOSBD
  • Running TOSBD for the First Time

Module 2: Building Our First Big Data Job

  • TOSBD – the Development Environment
  • HDFS Writer Job
  • Checking the Result in HDFS

Module 3: Formatting Data

  • Twitter Sentiment Analysis
  • Writing the Tweets in HDFS
  • Setting our Apache Hive Tables
  • Formatting Tweets with Apache Hive

Module 4: Processing Tweets with Apache Hive

  • Extracting Hashtags
  • Extracting Emoticons
  • Joining the Dots

Module 5: Aggregate Data with Apache Pig

  • Knowing About Pig
  • Extracting the Top Twitter Users
  • Extracting the Top Hashtags, Emoticons, and Sentiments

Module 6: Back to the SQL Database

  • Linking HDFS and RDBMS with Sqoop
  • Exporting and Importing Data to a MySQL Database

Module 7: Big Data Architecture and Integration Patterns

  • Streaming Pattern
  • Partitioning Pattern

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Who should attend this Data Integration and Big Data using Talend Course? 

This Data Integration and Big Data using Talend Course is designed for individuals who want to enhance their proficiency in managing and integrating data using the Talend platform. This course can benefit a wide range of professionals, including: 

  • Data Analysts
  • Data Engineers
  • IT Professionals
  • Business Analysts
  • Database Administrators
  • Software Developers
  • Project Managers

Prerequisites of the Data Integration and Big Data using Talend Course

There are no formal prerequisites for this Data Integration and Big Data using Talend Course. However, basic knowledge of Data Warehousing and SQL would be beneficial for delegates.

Data Integration and Big Data using Talend Course Overview

Data Integration and Big Data have become the driving force behind modern businesses, facilitating the seamless management and analysis of massive datasets. In an era where data is the currency of success, understanding how to harness its potential is paramount. This course provides an insightful journey into the world of Data Integration and Big Data using Talend, shedding light on its profound relevance.

Proficiency in Data Integration and Big Data is indispensable for a range of professionals, including data engineers, analysts, business intelligence specialists, and data scientists. Mastery of these subjects empowers individuals to efficiently process, combine, and analyse diverse data sources, enabling data-driven decision-making.

This intensive 2-day training is designed to equip delegates with a comprehensive understanding of Data Integration and Big Data using Talend. Through hands-on exercises and expert guidance, participants will gain practical skills to manage, transform, and extract insights from big data sources efficiently. By the end of the course, delegates will be well-prepared to tackle real-world data integration challenges and harness the power of Big Data in their professional endeavours.

Course Objectives:

  • To master the Talend ETL tool for data extraction, transformation, and loading
  • To learn to process and integrate data from diverse sources, including structured and unstructured data
  • To gain proficiency in Big Data concepts and tools like Hadoop and Spark
  • To develop skills to design and implement data integration solutions in real-world scenarios
  • To explore best practices for data quality, governance, and security in Big Data projects
  • To harness the power of Talend for data analytics and visualisation
  • To collaborate effectively with cross-functional teams in data-related projects

After successfully completing the Data Integration and Big Data using Talend course, delegates will acquire a robust skill set in working with Big Data and enhancing their professional credibility. This knowledge opens doors to exciting career opportunities in data-centric roles and provides a competitive edge, ensuring they stand out in the field.

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What’s included in this Data Integration and Big Data using Talend Course?

  • World-Class Training Sessions from Experienced Instructors    
  • Data Integration and Big Data using Talend Certificate 
  • Digital Delegate Pack

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Data Warehousing Training Course Outline

Module 1: Introduction to Data Warehouse

  • What is Data Warehousing?
  • Features of Data Warehouse
  • Types of Data Warehouse
  • Components of Data Warehouse
  • Use of Data Warehouse
  • Advantages of Data Warehouse
  • Disadvantages of Data Warehouse
  • Data Warehouse Tools
  • Data Warehouse Applications
  • Integrating Heterogeneous Databases

Module 2: Terminologies

  • Metadata
  • Metadata Repository
  • Data Cube
  • Data Mart
  • Virtual Warehouse

Module 3: Dimensions and Facts

  • Facts
  • Dimensions

Module 4: Modelling

  • Data Warehouse Modelling Overview
  • ER Diagram

Module 5: Delivery Process

  • Delivery Method
  • IT Strategy
  • Education and Prototyping
  • Technical Blueprint

Module 6: System Processes

  • Process Flow in Data Warehouse
  • Extract and Load Process
  • Clean and Transform Process
  • Backup and Archive the Data

Module 7: Data Warehouse Architecture

  • Three-Tier Data Warehouse Architecture
  • Data Warehouse Models
  • Load, Warehouse, and Query Manager

Module 8: Data Warehouse OLAP

  • Types of OLAP Servers
  • OLAP Operations
  • OLAP Vs OLTP

Module 9: Relational and Multidimensional OLAP

  • Relational OLAP
  • Multidimensional OLAP
  • Three-Tier Data Warehouse Architecture

Module 10: Data Warehouse Schemas

  • Star Schema
  • Snowflake Schema
  • Fact Constellation Schema
  • Schema Definition

Module 11: Horizontal and Vertical Partitioning

  • Introduction to Partitioning
  • Horizontal Partitioning
  • Vertical Partitioning

Module 12: Metadata Concepts

  • Metadata Categories
  • Role of Metadata

Module 13: System and Process Managers

  • System Managers
  • Process Managers

Module 14: Security and Backup

  • Security Requirements
  • User Access
  • Impact of Security on Design
  • Hardware and Software Backup

Module 15: Tuning and Testing

  • Tuning
  • Testing

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Who should attend this Data Warehousing Training Course?

The Data Warehousing Course is suitable for individuals who wish to enhance their understanding and proficiency in the field of Data Warehousing. This Data Warehousing Course can be beneficial for a wide range of professional, including:

  •  Data Professionals
  • Business Analysts
  • IT Managers
  • Software Developers
  • Business Intelligence Professionals
  • Project Managers
  • Database Professionals

Prerequisites of the Data Warehousing Training Course

There are no formal prerequisites for this Data Warehousing Training Course. However, a basic understanding of basic database concepts would be beneficial for delegates.

Data Warehousing Training Course Overview

Data Warehousing is the process of centralising, cleaning, and transforming data from multiple sources into a unified repository for analytical purposes It plays a pivotal role in collecting, storing, and managing vast amounts of data, enabling organisations to make informed decisions. This Data Warehousing Course provides delegates with a comprehensive understanding of data warehousing, including its significance in data analytics, business intelligence, and decision-making processes.

Proficiency in this Data Warehousing Course is essential for a wide range of professionals, including Data Analysts, Business Intelligence Experts, Database Administrators, and IT Managers. Data Warehousing proficiency empowers individuals to extract valuable insights from large datasets, enhance strategic planning, and make data-driven decisions.

The Knowledge Academy’s 1-day Data Warehousing Course is designed to equip delegates with the knowledge and practical skills needed to excel in data warehousing. Delegates will learn the fundamentals of data warehousing architecture, ETL (Extract, Transform, Load) processes, data modelling, and data warehouse design. Hands-on exercises and real-world case studies will provide a holistic understanding of data warehousing concepts.

Course Objectives

  • To understand the core concepts and principles of Data Warehousing
  • To learn how to design and implement an effective Data Warehousing system
  • To explore data modelling techniques for Data Warehousing
  • To gain proficiency in ETL processes and tools
  • To acquire knowledge of data warehouse management and maintenance
  • To analyse real-world case studies to apply data warehousing principles

After completing the Data Warehousing Course, delegates will receive a certification in Data Warehousing, validating their expertise in this critical field. This Data Warehousing Certification is recognised by industry leaders and will enhance career opportunities, enabling individuals to contribute effectively to their organisations.

 

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What’s included in this Data Warehousing Training Course?

  • World-Class Training Sessions from Experienced Instructors    
  • Data Warehousing Certificate 
  • Digital Delegate Pack

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Online Instructor-led (1 days)

Online Self-paced (8 hours)

ELK Stack Training Outline

Module 1: Introduction to ELK Stack

  • What is ELK Stack?
  • ELK Stack Architecture
  • Importance of ELK
  • Kibana
  • ELK Vs Splunk
  • Advantages and Disadvantages of ELK Stack

Module 2: Installing ELK

  • Environment Specifications
  • Java and Elasticsearch Installation

Module 3: Elasticsearch

  • Basic of Elasticsearch 
  • Elasticsearch Queries 
  • REST API
  • Plugins

Module 4: Logstash

  • Configuration
  • Pitfalls
  • Logstash Plugins

Module 5: Kibana

  • Kibana Searches
  • Visualisations
  • Dashboards
  • Kibana Elasticsearch Index

Module 6: Beats

  • Introduction to Beats
  • Configuration         
  • Modules

Module 7: ELK in Production

  • What is ELK Production?
  • Monitor Logstash/Elasticsearch Exceptions
  • Security
  • Maintainability
  • Upgrades
  • Use Cases

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Who should attend this ELK Stack Training Course? 

The ELK Stack Course is designed for individuals who aim to enhance their proficiency in working with the ELK Stack, which consists of Elasticsearch, Logstash, and Kibana. This course can benefit a wide range of professionals, including: 

  • Developers
  • Data Analysts
  • Security Analysts
  • Business Analysts
  • Technical Managers
  • Database Administrators
  • Quality Assurance Professionals

Prerequisites of the ELK Stack Training Course

There are no formal prerequisites for this ELK Stack Course. However, basic knowledge of JSON Data Format, SQL and Restful API would be beneficial for delegates.

 

ELK Stack Training Course Overview

The ELK Stack Training Course is designed to provide a comprehensive understanding of Elastic Stack, a powerful set of tools for data collection, search, and visualisation. Businesses and organisations rely on ELK Stack to efficiently manage and analyse vast amounts of data. Understanding this technology is of paramount importance as it forms the backbone of modern data analytics and operational monitoring.

Proficiency in ELK Stack is crucial for IT professionals, Data Analysts, System Administrators, and DevOps Engineers who seek to harness the power of log analysis, real-time monitoring, and data visualisation. With its applications in troubleshooting, security monitoring, and performance optimisation, mastering ELK Stack is a career-enhancing move for those seeking to stay competitive in the IT landscape.

This intensive 1-day training equips delegates with the skills to deploy, configure, and maintain ELK Stack. Delegates will gain hands-on experience in setting up data pipelines, creating visualisations, and utilising Elasticsearch, Logstash, and Kibana effectively. By the end of the training, delegates will be well-prepared to tackle real-world data challenges, enhancing their problem-solving abilities and job prospects.

Course Objectives:

  • To understand the core components of ELK Stack, including Elasticsearch, Logstash, and Kibana
  • To learn how to collect, parse, and index data for real-time search and analysis
  • To create custom dashboards and visualisations for monitoring and reporting
  • To troubleshoot common issues and optimise ELK Stack for performance
  • To secure ELK Stack deployments and manage access control
  • To utilise ELK Stack for log analysis, system monitoring, and security operations

Upon successfully finishing the ELK Stack Training Course, delegates will have acquired the skills necessary for proficiently deploying and managing ELK Stack. This knowledge will enable them to effectively utilise ELK Stack for data analytics, system monitoring, and security operations, making them valuable assets in their professional endeavors.

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What’s included in this ELK Stack Training Course?

  • World-Class Training Sessions from Experienced Instructors    
  • ELK Stack Certificate 
  • Digital Delegate Pack

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Online Instructor-led (2 days)

Online Self-paced (16 hours)

Hadoop Training Course with Impala Outline

Module 1: Introduction to Big Data and Hadoop

  • What is Big Data?
  • Characteristics and Challenges of Big Data
  • Understanding Hadoop as a Big Data Solution
  • Hadoop Ecosystem Overview

Module 2: Hadoop Distributed File System (HDFS)

  • Introduction to HDFS
  • HDFS Architecture
  • File Storage and Replication
  • Data Ingestion into HDFS
  • Managing Data in HDFS

Module 3: Hadoop MapReduce

  • MapReduce Basics
  • MapReduce Workflow
  • Writing and Running MapReduce Jobs
  • Hadoop Streaming and Custom MapReduce
  • MapReduce Optimisation Techniques

Module 4: Hive - Data Warehousing and Querying

  • Introduction to Hive
  • Hive Data Model and Schema Design
  • Hive Query Language (HQL)
  • Managing Tables and Databases in Hive
  • Hive UDFs and Custom Functions

Module 5: Pig - Data Flow and Scripting

  • Introduction to Pig
  • Pig Latin Language
  • Loading, Transforming, and Storing Data with Pig
  • Pig UDFs and User-Defined Functions

Module 6: Introduction to Impala

  • What is Impala?
  • Impala Vs Hive and Pig
  • Impala Architecture
  • Interactive Querying with Impala
  • Supported Data Formats and Sources

Module 7: Impala Querying Basics

  • Writing and Running Impala Queries
  • SQL Syntax in Impala
  • Query Optimisation in Impala
  • Working with Tables and Views
  • Impala Performance Tuning

Module 8: Advanced Impala Optimisation

  • Impala Data Types and Functions
  • Complex Queries and Aggregations
  • Impala Partitioning and Clustering
  • Impala Security and Access Control
  • Integrating Impala with Other Hadoop Components

Module 9: Data Ingestion and ETL with Hadoop

  • Data Ingestion Strategies
  • ETL (Extract, Transform, Load) Processes with Hadoop
  • Using Apache Nifi for Data Ingestion
  • Working with Hadoop's Ecosystem Tools
  • Real-time Data Processing with Hadoop and Impala

Module 10: Machine Learning with Hadoop and Impala

  • Introduction to Machine Learning and Data Science
  • Machine Learning Libraries in Hadoop
  • Building and Training Machine Learning Models
  • Deploying Machine Learning Models with Impala

Module 11: Data Visualisation and Reporting

  • Data Visualisation Tools for Hadoop
  • Creating Interactive Dashboards
  • Reporting and Analytics in Hadoop
  • Integrating Impala with BI Tools
  • Building Data Reports and Dashboards

Module 12: Hadoop Security and Optimisation

  • YARN (Yet Another Resource Negotiator)
  • Resource Management
  • Hadoop Security
  • Hadoop Cluster Optimisation
  • Hadoop High Availability and Disaster Recovery
  • Hadoop and Cloud Integration

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Who should attend this Hadoop Training Course with Impala?

The Hadoop Training Course with Impala is a specialised course designed to teach the fundamentals of Hadoop and Impala, two powerful tools in the Big Data ecosystem. The following are some of the professionals who can benefit from this course:

  • Data Analysts
  • Software Developers
  • Database Administrators
  • Business Analysts
  • System Administrators
  • Data Scientists
  • Project Managers
  • Quality Analysts

Prerequisites of the Hadoop Training Course with Impala

There are no formal prerequisites for this Hadoop Training Course with Impala. However, a basic understanding of data analysis would be beneficial for the delegates.

 

Hadoop Training Course with Impala Overview

Mastering Hadoop and Impala has become indispensable for professionals aiming to thrive in data-centric industries. This comprehensive training course delves into the heart of Hadoop and Impala technologies, unravelling their significance in handling vast datasets efficiently. With the explosion of data, businesses seek experts who can harness these tools, making this training more pertinent than ever.

Proficiency in Hadoop and Impala is paramount for data engineers, analysts, and IT professionals striving for excellence in data processing. Organisations depend on these technologies to gain actionable insights. Mastering Hadoop and Impala empowers professionals to navigate complex data landscapes, making them indispensable assets for any data-driven enterprise.

This intensive 2-day training equips delegates with hands-on experience in Hadoop and Impala, enhancing their ability to process, analyse, and interpret vast datasets efficiently. Through interactive sessions and real-world examples, delegates learn to optimise queries, troubleshoot issues, and design robust data processing pipelines, ensuring they are well-prepared for the challenges.

Course Objectives:

  • To master the techniques for processing large datasets using Hadoop
  • To develop advanced skills in Impala for high-speed data querying
  • To gain hands-on experience in Hadoop ecosystem components like HDFS and MapReduce
  • To learn to optimise Impala queries for improved performance
  • To explore data ingestion and storage strategies in Hadoop
  • To understand security and data governance best practices

After completing this course, delegates receive a certification validating their expertise in Hadoop and Impala technologies. This certification not only demonstrates their proficiency but also opens doors to a plethora of opportunities in data engineering, analytics, and business intelligence.

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What’s included in this Hadoop Training Course with Impala?

  • World-Class Training Sessions from Experienced Instructors
  • Hadoop Training Course with Impala Certificate
  • Digital Delegate Pack

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Online Instructor-led (1 days)

Online Self-paced (8 hours)

HBase Training Course Outline

Module 1: Introduction to HBase

  • What is HBase?
  • HBase and HDFS
  • Storage Mechanism in HBase
  • Column Oriented and Row Oriented
  • HBase and RDBMS
  • Applications of HBase
  • Architecture
  • Installation

Module 2: Shell and General Commands

  • HBase Shell
  • General Commands
    • status
    • version
    • table_help
    • whoami
  • Data Definition Language
  • Data Manipulation Language
  • Starting HBase Shell
  • Admin API

Module 3: HBase Table

  • Create
  • Listing
  • Disabling and Enabling
  • Describe and Alter
  • Exists
  • Drop
  • Count and Truncate Commands

Module 4: Client API and Data

  • Class HBase Configuration
  • Class HTable
  • Class Put and Get
  • Class Result
  • Data
    • Create
    • Update
    • Read
    • Delete

Module 5: HBase Scan

  • Scan Using
    • HBase Shell
    • Java API

Module 6: Security

  • grant
  • revoke
  • User permission

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Who should attend this HBase Training Course?

The HBase Course is designed to impart skills and knowledge to understand and use HBase, a NoSQL Database, to handle vast amounts of data. This course can be beneficial for a wide range of professionals, including:

  • Data Engineers
  • Database Administrators
  • Software Developers
  • Data Scientists
  • System Architects
  • Business Analysts
  • Quality Assurance Engineers

Prerequisites of the HBase Training Course

There are no formal prerequisites for this HBase Course. However, a basic understanding of Hadoop Architecture and APIs would be beneficial for delegates.

HBase Training Course Overview

HBase is a NoSQL database, and Impala, an analytic query engine, are crucial components of the Hadoop ecosystem. They enable efficient storage and real-time data processing, making them indispensable for data professionals and organisations. This course is designed to provide a comprehensive understanding of these technologies and their integration, allowing learners to harness their power for data management and analysis.

Proficiency in HBase and Impala is essential for individuals working in the fields of data engineering, data analysis, and data science. Professionals who aim to excel in data storage, retrieval, and analysis need to master HBase and Impala to unlock their full potential. This course empowers database administrators, data engineers, and data analysts to enhance their skills and meet the growing demands of the data industry.

This intensive 1-day training course is designed to provide delegates with hands-on experience in deploying and managing HBase and Impala. Delegates will gain practical knowledge in setting up HBase clusters, importing data, and optimising performance. They will learn how to use Impala for real-time query processing, thus improving their data analysis capabilities.

Course Objectives:

  • To understand the fundamentals of HBase, its architecture, and data modelling
  • To learn to set up and configure HBase clusters for efficient data storage
  • To gain expertise in data import and export operations in HBase
  • To explore the basics of Impala and its integration with HBase for analytics
  • To perform real-time queries using Impala, enhancing data analysis capabilities
  • To optimise HBase and Impala for improved performance and scalability

After completing the HBase Training Course with Impala, delegates will receive a certification that validates their expertise in HBase and Impala. This certification is a valuable asset, showcasing your ability to handle big data solutions and make informed data-driven decisions.

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What’s included in this HBase Training Course?

  • World-Class Training Sessions from Experienced Instructors 
  • HBase Certificate
  • Digital Delegate Pack

Show moredown

Online Instructor-led (2 days)

Online Self-paced (16 hours)

Informatica PowerCenter Training Course Outline

Module 1: Introduction to Informatica

  • Introduction
  • Use Cases for Informatica

Module 2: Informatica Architecture

  • Architecture of Informatica
  • Informatica ETL Tool
  • Informatica Domain
  • Node
  • PowerCenter Repository
  • Domain Configuration
  • PowerCenter Client and Server Connectivity
  • Repository and Integration Service

Module 3: Installing Informatica PowerCenter

  • Install Oracle
    • Database 11g R2
    • SQL Developer
  • Install Informatica
  • Set Up SQL Developer Domain and Repository
  • Install Informatica Server and Client

Module 4: Configuring Clients and Repositories

  • Overview of Informatica Domain
  • Opening the Administrator Home Page
  • Creating Repository Services
  • Configuring Client and Domain
  • Creating User

Module 5: Source Analyser and Target Designer

  • Opening a Source Analyser
  • Importing a Source Table in Source Analyser
  • Opening a Target Designer and Importing Target in Target Designer
  • Creating a Folder

Module 6: Mappings

  • Overview of Mappings
  • Components of Mapping
  • Create a Mapping
  • Mapping Parameters and Variables

Module 7: Workflow and Workflow Monitor

  • Introduction to Workflow
  • How to Open Workflow Monitor?
  • Views in Workflow Monitor

Module 8: Debug Mappings

  • Introduction
  • Steps to Use Debugger Mappings

Module 9: Transformations

  • Introduction to Transformations
  • Classification of Transformation
  • Transformation
    • Filter
    • Source Qualifier and Aggregator
    • Router and Joiner
    • Rank
    • Sequence Generator
    • Transaction Control
    • Lookup and Re-Usable
    • Normaliser
  • Performance Tuning for Transformation

 

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Who should attend this Informatica PowerCenter Training Course?

The Informatica PowerCenter Training Course is designed to impart essential skills to work with Informatica PowerCenter, a leading Data Integration tool. The course covers a range of topics helping learners to Extract, Transform, and Load (ETL) data from different sources to a Data Warehouse. This course can be beneficial for a wide range of professionals, including:

  • Data Integration Specialists
  • ETL Developers
  • Database Administrators
  • Business Intelligence Professionals
  • Data Architects and Analysts
  • System Administrators
  • Solution Architects

Prerequisites of the Informatica PowerCenter Training Course

There are no formal prerequisites for this Informatica PowerCenter Course. However, a basic knowledge of SQL would be beneficial for delegates.

Informatica PowerCenter Training Course Overview

The Informatica PowerCenter Training Course is a comprehensive designed to equip individuals with the essential skills required to harness the power of Informatica PowerCenter. Informatica PowerCenter is the cornerstone of ETL (Extract, Transform, Load) processes, making it highly relevant for anyone involved in data management, analytics, or business intelligence.

Proficiency in this course is crucial for data professionals, ETL developers, data architects, and business intelligence specialists. It empowers professionals to extract, transform, and load data from various sources efficiently, ensuring data accuracy, consistency, and reliability. Organisations highly value individuals who can navigate and optimise the PowerCenter, which is central to maintaining integrity and usability.

This intensive 2-day training will empower delegates with hands-on experience using Informatica PowerCenter. Delegates will learn to create, schedule, and monitor data workflows, enhancing their integration and transformation capabilities. They'll gain insights into best practices, optimising performance, and troubleshooting issues, making them more efficient and effective in their roles.

Course Objectives:

  • To understand the fundamentals of Informatica PowerCenter
  • To create and manage ETL workflows using PowerCenter
  • To optimise data integration processes for improved performance
  • To troubleshoot common issues and errors
  • To integrate data from various sources, including databases and cloud platforms
  • To ensure data quality and consistency throughout the ETL process
  • To develop proficiency in using Informatica PowerCenter's tools and features
  • To apply best practices in data integration and transformation

After completing the Informatica PowerCenter Training Course, delegates will receive a certification that validates their expertise in using Informatica PowerCenter for data integration and transformation. This certification is a valuable asset, demonstrating their proficiency to employers and colleagues and opening doors to exciting career opportunities.

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What’s included in this Informatica PowerCenter Training Course?

  • World-Class Training Sessions from Experienced Instructors 
  • Informatica PowerCenter Certificate 
  • Digital Delegate Pack

Show moredown

Online Instructor-led (2 days)

Online Self-paced (16 hours)

Spark Training for Python Developers Course Outline

Module 1: Set Up a Spark Virtual Environment

  • Data-Intensive Applications Architecture
  • Overview of Spark
  • Introduction to Anaconda
  • Setting a Spark Powered Environment
  • Building App with PySpark
  • Virtualising the Environment with Vagrant
  • Moving to the Cloud

Module 2: Building Batch and Streaming Apps with Spark

  • Architecting Data-Intensive Apps
  • Analysing the Data
  • Exploring GitHub

Module 3: Juggling Data with Spark

  • Serialising and Deserialising Data
  • Storing and Deleting Data
  • Exploring Data Using
    • Blaze
    • Spark SQL

Module 4: Data Using Spark

  • Classifying Spark MLlib Algorithms
  • Spark MLlib Data Types
  • Clustering Twitter Dataset
  • Build Machine Learning Pipelines

Module 5: Streaming Live Data with Spark

  • Streaming Architecture
  • Process Live Data with TCP Sockets
  • Build a Reliable and Scalable Streaming App
  • Lambda and Kappa Architecture

Module 6: Visualising Insights and Trends

  • Pre-process Data for Visualisation
  • Creating Wordclouds

 

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Who should attend this Spark Training for Python Developers Course?

The Spark Training for Python Developers Course is a specialised course aimed at Python Developers keen to enhance their skills in Big Data processing using Apache Spark. This course can be beneficial a wide range of professionals, including:

  • Python Developers
  • Data Scientists
  • Machine Learning Engineers
  • Data Engineers
  • Data Analysts
  • DevOps Engineers
  • Project Managers

Prerequisites of the Spark Training for Python Developers Course

There are no formal prerequisites for this Spark Training for Python Developers Course. However, a basic understanding of SQL and Python programming would be beneficial for delegates.  

Spark Training for Python Developers Course Overview

The Spark Training for Python Developers Course provides a comprehensive understanding of Spark and its integration with Python, emphasising its relevance in harnessing big data, conducting efficient data processing, and unlocking powerful analytics and machine learning capabilities. As organisations continue to rely on data-driven decisions, proficiency in Spark for Python developers is a must-have skill.

Proficiency in Apache Spark is crucial for Data Engineers, Data Scientists, and Software Developers who aspire to work with big data, streamline data processing pipelines, and build scalable machine learning models. With the exponential growth of data, the ability to harness Spark's processing power and flexibility becomes paramount for professionals looking to enhance their career prospects in the data industry.

This intensive 2-day training equips delegates with the knowledge and practical skills needed to leverage Apache Spark effectively with Python. Delegates will gain hands-on experience in data manipulation, distributed computing, and creating data pipelines, ensuring they are well-prepared to tackle real-world big data challenges. By the end of the course, delegates will be able to develop Spark applications in Python, optimise data processing tasks, and execute advanced analytics with confidence.

Course Objectives:

  • To gain a solid understanding of Apache Spark and its ecosystem
  • To develop proficiency in using Python to interact with Spark
  • To learn to process and analyse big data efficiently
  • To master the art of creating data pipelines using Spark
  • To explore machine learning and advanced analytics with Spark and Python
  • To understand the best practices for optimising Spark applications
  • To acquire practical knowledge to solve real-world data challenges
  • To enhance your ability to work with distributed computing frameworks

After completing the course, delegates will receive a certification that validates their skills and knowledge. This certification is a valuable asset for your career, demonstrating your expertise in big data processing and analytics and opening doors to exciting opportunities in the data industry.

 

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What’s included in this Spark Training for Python Developers Course?

  • World-Class Training Sessions from Experienced Instructors 
  • Spark Training for Python Developers Certificate 
  • Digital Delegate Pack

Show moredown

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Apache ORC Training​ Course Outline

Module 1: Introduction to Apache ORC

  • What is Apache ORC?
  • ORC Adapters
  • ORC Types
  • Level of Indexes
  • ACID Support

Module 2: Building ORC

  • Building
    • Both C++ and Java
    • Java
    • C++
    • Specify Third-Party Libraries for C++ Build

Module 3: Using in Spark

  • Spark DDL
  • Spark Configuration

Module 4: Using in Python

  • PyArrow
  • Dask

Module 5: Using in Hive

  • Hive DDL
  • Hive Configuration
    • Table Properties
    • Configuration Properties

Module 6: Using in MapReduce

  • Reading ORC Files
  • Writing ORC Files
  • Sending OrcStruct, OrcList, OrcMap, or OrcUnion through the Shuffle

Module 7: Using ORC Core

  • Core Java
  • Core C++

Module 8: Apache ORC Tools

  • C++ Tools
    • orc-contents
    • orc-metadata
    • csv-import
    • orc-scan
    • orc-statistics
  • Java Tools
    • Java Meta
    • Java Data and Scan
    • Java Convert
    • Java JSON Schema    

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Who should attend this Apache ORC Training Course?

The Apache Optimised Row Columnar (ORC) Training is a specialised course aimed to provide Engineers, Architects, and Developers with an in-depth understanding of high-performance columnar storage format used in the Hadoop ecosystem. The following are some professionals who can benefit from this course:

  • Data Engineers
  • Big Data Developers
  • Database Administrators
  • Data Scientists
  • Hadoop Administrators
  • Cloud Engineers
  • ETL Developers

Prerequisites of the Apache ORC Training Course

There are no formal prerequisites for this Apache ORC Training Course. However, a basic understanding of Hadoop would be useful.

Apache ORC Training​ Course Overview

Apache is a non-profit organisation that helps those open-source software projects that are released under the license of Apache. Apache ORC is a self-describing columnar file format enabling efficient querying and storage of data on Hadoop. It uses multi-version concurrency control for supporting ACID transactions. This Apache ORC Training is designed to equip delegates with a detailed knowledge of Apache ORC.

The Knowledge Academy’s Apache OCR Training will introduce delegates to ORC adapters and types. Delegates will gain knowledge of Apache ORC’s three levels of indexes. In addition, delegates will learn how to build Apache ORC. Delegates will get familiarised with hive DDL and configuration, including table and configuration properties.

During this 1-day course, delegates will learn how to read and write ORC files. Delegates will get an understanding of how to send OrcStruct, OrcList, OrcMap through the shuffle. This Apache ORC Training will fully prepare delegates on how to use Apache ORC tools – C++ and Java tools. Post completion of this training, delegates will be able to use        Java meta, data, scan, convert, and JSON Schema.

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What’s included in this Apache ORC Training Course?

  • World-Class Training Sessions from Experienced Instructors  
  • Apache ORC Certificate  
  • Digital Delegate Pack

Show moredown

Online Instructor-led (2 days)

Online Self-paced (16 hours)

Apache Spark and Scala Training​ Course outline

Module 1: Introduction to Scala

  • Introduction to Scala and Development of Scala for Big Data Applications
  • Apache Spark

Module 2: Pattern Matching

  • Introduction to Pattern Matching
  • Uses of Scala
  • Concept of REPL (Read Evaluate Print Loop)
  • Deep Drive into Scala Pattern Matching
  • Type Interface and Higher-Order Function
  • Currying and Traits

Module 3: Executing the Scala Code

  • Introduction to Scala Interpreter
  • Creating Static Members with Companion Objects
  • Implicit Classes in Scala
  • Different Classes in Scala

Module 4: Classes Concepts in Scala

  • Understanding the Constructor Overloading
  • Different Abstract Classes
  • Hierarchy Types in Scala
  • Concept of Object Equality and Val and Var Methods in Scala​

Module 5: Concepts of Traits with Example

  • Introduction to Traits in Scala ​
  • When to Use Traits?​
  • Linearisation of Traits and the Java Equivalent ​
  • Boilerplate Code​

Module 6: Scala Java Interoperability and Scala Collection​

  • Implementation of Traits in Scala and Java​
  • Handling of Multiple Traits Extending​
  • Introduction to Scala Collections​
  • Classification of Collections ​
  • Difference Between Iterator and Iterable in Scale
  • List and Sequence in Scala

Module 7: Mutable Collections vs Immutable Collections

  • Types of Collections in Scala
  • Lists and Arrays in Scala
  • List Buffer and Array Buffer
  • Queue in Scala
  • Stacks and Sets
  • Maps and Tuples in Scala

Module 8: Introduction to Spark

  • What are Spark and Spark Stack?
  • Ways to Resolve Hadoop Drawbacks
  • Interactive Operations on Map Reduce
  • Spark Hadoop YARN
  • HDFS and YARN Revision
  • How it is Better Hadoop?
  • Deploying Spark Without Hadoop
  • Spark History Server
  • Cloudera Distribution

Module 9: Spark Basics

  • Spark Installation
  • Memory Management
  • Concept of Resilient Distributed Datasets (RDD)​
  • Functional Programming in Spark​

Module 10: Working with RDDs in Spark​

  • Creating RDDs ​
  • Operations and Transformation in RDD ​
  • RDD Partitioning ​
  • FlatMap Method ​
  • Scala Map Count ​
  • Saveastextfiles
  • Pair RDD Functions

Module 11: Aggregating Data with Pair RDDs ​

  • Introduction to Key-Value Pair in RDDs ​
  • How Spark Makes Map-Reduce Operations Faster?​

Module 12: Writing and Deploying Spark Applications​

  • Difference Between Spark and Scala
  • Set and Set Operations
  • List and Tuple
  • Concatenating List
  • Install Apache Maven

Module 13: Parallel Processing

  • Spark Parallel Processing
  • Setup Spark Master Code
  • Introduction to Spark Partitions
  • Data Locality in Hadoop
  • Comparing Repartition and Coalesce
  • Actions of Spark

Module 14: Spark RDD Persistence

  • Execution Flow in Spark
  • RDD Persistence Overview
  • Spark Terminology
  • Distribution Shared Memory vs RDD
  • ReduceByKey and SortByKey and AggregateByKey

Module 15: Spark Streaming and Mila

  • Introduction to Spark Streaming
  • What is Spark Streaming?
  • Aspects of Spark Streaming
  • How does Spark Streaming Work?
  • Broadcast Variables
  • Accumulator

Module 16: Spark Variables and RDD Operations

  • Variables in Spark
  • Numeric RDD Operations

Module 17: Scheduling or Partitioning

  • Partitioning in Spark
  • Hash Partition and Range Partition
  • Scheduling within and Around Applications
  • Map Partition with Index
  • GroupByKey
  • Spark Master High Availability
  • Standby Masters with Zookeeper

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Who should attend this Apache Spark and Scala Training Course?

The Apache Spark and Scala Training Course is a specialised  that helps professionals to gain expertise in the Big Data Analytics and Distributed Computing sector. This course can be beneficial for a wide range of professionals, including:

  • Software Developer
  • Data Scientists
  • Data Engineers
  • Business Analysts
  • Systems Architects
  • Database Administrators
  • Data Journalists
  • Project Managers

Prerequisites of the Apache Spark and Scala Training Course

For attending this Apache Spark and Scala Training Course, a basic knowledge of Java, Database, Query Language, and SQL would be beneficial for delegates.

 

Apache Spark and Scala Training Course Overview

Apache Spark and Scala have emerged as pivotal tools in the world of Big Data Processing and Analytics. Apache Spark is a robust open-source data processing framework combined with Scala, a high-performance programming language that offers a scalable solution. This course is designed for software developers and IT professionals who can benefit from understanding these technologies to build efficient data processing pipelines.

Proficiency in Apache Spark and Scala is crucial in today's data-driven landscape. It empowers data engineers, data scientists, and analysts to process and analyse large datasets swiftly, enabling data-driven decision-making. For professionals in fields like data science, machine learning, and big data analytics, mastering Spark and Scala is essential.

This intensive 2-day training is designed to provide delegates with a solid foundation in Apache Spark and Scala. Delegates will gain hands-on experience in working with these technologies, learning to develop efficient data processing pipelines, working with distributed datasets, and applying advanced analytics techniques. The course combines theoretical knowledge with practical exercises, ensuring that delegates can immediately apply what they learn in their professional roles.

Course Objectives:

  • To learn how to work with distributed data using Spark RDDs
  • To explore Spark's DataFrame and Dataset APIs for structured data processing
  • To master the art of data manipulation, transformation, and analysis with Spark
  • To develop Spark applications and perform data processing tasks
  • To discover the integration of Spark with popular data sources and tools
  • To implement real-world use cases and best practices for Spark and Scala

Upon completing this course, delegates will benefit from a solid foundation in Apache Spark and Scala. They will possess the practical skills and knowledge required to handle and analyse big data effectively, enabling them to excel in their data analytics roles. This course is a valuable investment in their professional development and opens doors to various opportunities in the world of big data analytics.

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What’s included in this Apache Spark and Scala Training Course?

  • World-Class Training Sessions from Experienced Instructors 
  • Apache Spark and Scala Certificate 
  • Digital Delegate Pack

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Online Instructor-led (2 days)

Online Self-paced (16 hours)

Mastering Apache Ambari Training Course Outline

Module 1: Introducing Ambari Administration

  • Understanding Ambari Terminology
  • Using the Administrator Role in Ambari Web
  • Setting up Ambari to Use an Internet Proxy Server
  • Managing Cluster Roles
  • Managing Versions
  • Managing Local Users
  • Managing Local Group Membership
  • Installing Ambari Agents Manually
  • Understanding Service Users and Groups
  • Understanding Custom and Private Host Names
  • Moving the Ambari Server
  • Configuring LZO Compression
  • Using LZO Compression with Hive Queries
  • Using an Existing or Installing a Default Database
  • Configuring Network Port Numbers
  • Tuning Ambari Performance
  • Customising Ambari Log and pid Directories
  • Managing Host Participation for HDFS and YARN

Module 2: Managing and Monitoring Your Hadoop Cluster

  • Introducing Ambari Operations
  • Working with the Cluster Dashboard
  • Modifying the Cluster Dashboard
  • Managing Hosts
  • Establishing Rack Awareness
  • Managing Services
  • Managing Service Configuration Settings
  • Managing Service Configuration Versions
  • Managing HDFS
  • Start Kerberos Wizard from Ambari Web
  • Configuring Log Settings
  • Managing Host Configuration Groups
  • Managing Alerts and Notifications
  • Predefined Alerts

Module 3: Managing High Availability of Services

  • Managing High Availability
    • Enabling AMS
    • Configuring NameNode
    • Configuring ResourceManager
    • Configuring HBase Setting Up Multiple HBase Masters Manually
    • Configuring Hive
    • Configuring Storm
    • Configuring Oozie
    • Configuring Atlas
    • Enabling Ranger admin

Module 4: Using Ambari Core Services

  • Using Ambari Core Services
    • Understanding Ambari Metrics System
    • Grafana Dashboards Reference
    • Tuning Performance for AMS
    • Setting up AMS Security
    • Understanding Ambari log Search
    • Understanding Ambari Infra
    • Tuning Performance for Ambari Infra

Module 5: Administering Ambari Views

  • Understanding Ambari Views
  • Ambari Views Terminology
  • Increase Memory Available to Ambari Views Server
  • Review the Number of Expected Concurrent Ambari Views Users
  • Configure a Trust Store for the Ambari Views Server
  • Increase Timeout Value for Ambari Views Server
  • Run a Remote, Standalone Ambari Views Server
  • Comparing Standalone and Operational Ambari Server Set Up
  • Running Standalone Ambari Views Servers behind a Reverse Proxy
  • Prepare to Set Up a Remote, Standalone Ambari Views Server
  • Configuring Ambari View Instances
  • Create an Ambari View Instance
  • Migrate Ambari View Instance Data
  • Create an Ambari View URL
  • Set Ambari View Permissions
  • Configure Ambari Views for Kerberos

Module 6: Configuring Ambari Views

  • Configuring Specific Views
  • Configuring Capacity Scheduler View
  • Configure Your Cluster for Files View
  • Create and Configure a Files View Instance
  • Set Up Kerberos for Files View
  • Configure Local Option for Files View
  • Configure Custom Option for Files View
  • Configuring Pig View
  • Configuring SmartSense View
  • Configure Workflow Manager View

Module 7: Using an Ambari View

  • Using YARN Queue Manager View
  • Using Files View
  • Using SmartSense View
  • Using Workflow Manager View

Module 8: Workflow Management

  • Workflow Manager Basics
  • Content Roadmap for Workflow Manager
  • Designing Workflows Using the Design Component
  • Monitoring Jobs Using the Dashboard
  • Sample ETL Use Case
  • Workflow Parameters
  • Settings Menu Parameters
  • Job States
  • Workflow Manager Files

 

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Who should attend this Mastering Apache Ambari Training Course?

The Mastering Apache Ambari Course is designed for professionals who aim to become proficient in managing and monitoring Hadoop clusters using Apache Ambari. This course can be beneficial for a wide range of professionals, including:

  • System Administrators
  • Big Data Engineers
  • Data Architects
  • DevOps Engineers
  • Hadoop Administrators
  • Project Managers
  • Security Officers

Prerequisites of the Mastering Apache Ambari Training Course

There are no formal prerequisites for attending this Mastering Apache Ambari Training Course.However, a basic knowledge of Management Tools Architecture, General Relational Databases, Hadoop, and basic UNIX would be beneficial for delegates.

 

Mastering Apache Ambari Training Course Overview

Apache Ambari is a crucial tool in the field of Big Data management and administration. With the exponential growth of data, organisations are increasingly relying on tools like Ambari to manage, monitor, and maintain their Hadoop clusters efficiently. This course offers an in-depth understanding of Apache Ambari and its relevance in modern data management and analytics.

Proficiency in Apache Ambari is vital for IT professionals, system administrators, and data engineers working with Big Data technologies. It's essential to master Apache Ambari because it simplifies cluster provisioning, monitoring, and management, leading to increased operational efficiency and reduced downtime.

This intensive 2-day training is designed to provide delegates with a comprehensive understanding of Apache Ambari. Delegates will learn how to install, configure, and manage Hadoop clusters effectively using Ambari. Delegates can expect hands-on experience, real-world scenarios, and best practices, ensuring that they are well-prepared to tackle the challenges of managing Big Data infrastructure.

Course Objectives:

  • To understand the fundamentals of Apache Ambari and its role in Big Data management
  • To gain proficiency in cluster installation and configuration using Ambari
  • To develop troubleshooting skills to minimise cluster downtime and issues
  • To implement security measures and user authentication in Hadoop clusters
  • To get hands-on experience with real-world use cases and scenarios
  • To acquire the knowledge and skills needed to excel in data infrastructure and administration roles

After completing the course, delegates will receive a certification in Mastering Apache Ambari. This certification is an asset, recognised in the industry, and can enhance your career prospects. It signifies your proficiency in Apache Ambari, making you a sought-after professional in the field of Big Data management and administration.

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What’s included in this Mastering Apache Ambari Training Course?

  • World-Class Training Sessions from Experienced Instructors  
  • Mastering Apache Ambari Certificate  
  • Digital Delegate Pack

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Online Instructor-led (2 days)

Online Self-paced (16 hours)

Apache Maven Training Course Outline

Module 1: Introductions

  • Build Lifecycle
  • POM
  • Profiles
  • Repositories
  • Standard Directory Layout
  • Dependency Mechanism
    • Optional Dependencies and Dependency Exclusions

Module 2: Plugins

  • Plugin Development
  • Configuring Plug-ins
  • Plugin Prefix Resolution
  • Developing Java Plugins

Module 3: Site

  • Creating a Site
  • APT Format
  • Snippet Macro

Module 4: Archetypes

  • What is an Archetype?
  • Creating Archetypes

Module 5: Repositories

  • Installing 3rd party JARs to Local Repository
  • Deploying 3rd party JARs to Remote Repository
  • Repository Management
  • Using Multiple Repositories
  • Large Scale Centralised Deployments
  • Mirror Settings
  • Deployment and Security Settings
  • Using Proxies
  • Authenticated HTTPS
  • Remote repository access through authenticated HTTPS
  • Relocation

Module 6: Maven Tools and IDE Integration

  • Maven Auto-Completion Using BASH

Module 7: Maven Community

  • What is the Maven Community?
  • Helping with Maven
  • Guide for New Committers
  • Testing Development Versions of Plugins
  • 3rd Party Resources

Module 8: Conventions

  • Maven Conventions
  • Naming Conventions
  • When You Can't Use the Conventions

Module 9: The Central Repository

  • Introduction to the Central Repository
  • Uploading Artefacts to the Central Repository
  • Improving the Repository

Module 10: Javadoc API

  • Maven Artefact
  • Maven Reporting
  • Maven Plugin API
  • Maven Model
  • Maven Core
  • Maven Settings

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Who should attend this Apache Maven Training Course?

The Apache Maven Course aims to equip you Software Developers, Build Managers, and Quality Assurance Engineers with the skills to master Maven – a powerful Project Management and Comprehension tool. The following are some professionals who can benefit from this course:

  • Software Developers
  • Build and Release Engineers
  • QA Engineers
  • DevOps Professionals
  • Project Managers
  • Application Support Engineers
  • System Architects

Prerequisites of the Apache Maven Training Course

There are no formal prerequisites for this Apache Maven Course.

Apache Maven Training ​Course Overview

Apache Maven is most popular build automation tool which is used for java projects. It is also a most powerful project management tool based on project object model (POM). In this 2-day Apache Maven Training delegates will learn how to solve problems related to software project builds and implement the Maven repository. From this training delegates will also learn about:

  • How to manage and create projects with java
  • Understanding the Maven Repository and Lifecycle
  • How to Installing Apache Maven
  • how to set up the Maven environment
  • Understand the profile activation via properties and environment
  • Using report plugins and how to creating custom pages

Throughout this training, delegates will understand about how to install and deploy a plugin with how to generate reports on code when developers are running into problems. After completing this training, delegates will be able to create a project website and release Maven artifacts.

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What’s included in this Apache Maven Training Course? 

  • World-Class Training Sessions from Experienced Instructors 
  • Apache Maven Certificate 
  • Digital Delegate Pack

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Online Instructor-led (2 days)

Online Self-paced (16 hours)

Splunk Training Course Outline

Module 1: Splunk Overview

  • Introduction to Splunk
  • Installing Splunk
  • Adding Data in Splunk

Module 2: Splunk Search Processing Language

  • Pipe Operator
  • Time Modifiers
  • Understanding Basic SPL
  • Sorting Results
  • Commands
    • Filtering
    • Reporting
  • Filtering, Modifying, and Adding Fields
  • Grouping Results

Module 3: Macros, Field Extraction, and Field Aliases

  • Field Extraction in Splunk
  • Macros
  • Field Aliases in Splunk
  • Splunk Search Query

Module 4: Tags, Lookups, and Correlating Events

  • Lookups
  • Tags
  • Reporting
  • Alerts

Module 5: Data Models, Pivot, and CIM

  • Understanding Data Models and Pivot
  • Event Actions in Splunk
  • Common Information Model in Splunk

Module 6: Knowledge Managers and Dashboards in Splunk

  • Role of a Knowledge Manager
  • Dashboards
  • Dynamic Form-Based Dashboards

Module 7: Splunk Licenses, Indexes, and Role Management

  • Buckets
  • Understanding journal. gz, .tsidx, and Bloom Filters
  • Splunk Licenses
  • Managing Splunk Licenses
  • License Pooling
  • Managing Indexes in Splunk
  • User Management

Module 8: Machine Data Using Splunk Forwarder and Clustering

  • Splunk Universal Forwarder
  • Splunk’s Light and Heavy Forwarders
  • Forwarder Management
  • Indexer Clusters
  • Lightweight Directory Access Protocol (LDAP)
  • Security Assertion Markup Language (SAML)

Module 9: Advanced Data Input in Splunk

  • Compress the Data Feed
  • Indexer Acknowledgment
  • Securing the Feed
  • Queue Size
  • Input
    • Monitor
    • Scripted
    • Network
  • Pulling Data Using Agentless Input

Module 10: Splunk’s Advanced .conf File and Diag

  • Understanding Splunk .conf Files
  • Setting Fine-Tuning Input
  • Anonymising the Data
  • Understanding Merging Logic in Splunk
  • Debugging Configuration Files
  • Creating a Diag

Module 11: Infrastructure Planning with Indexer and Search Head Clustering

  • Capacity Planning for Splunk Enterprise
  • Configuring 
    • Search Peer
    • Search Head
  • Search Head Clustering
  • Multisite Indexer Clustering
  • Splunk Architecture Practices

Module 12: Troubleshooting in Splunk

  • Monitoring Console
  • Log Files for Troubleshooting
  • Metrics.log File
  • Job Inspector
  • Troubleshooting
    • License Violations
    • Deployment Issues
    • Clustering Issues

Module 13: Advanced Deployment

  • Deploying Apps Through the Deployment Server
  • Creating a Server Group Using ServerClass.conf
  • Deploy Configuration File Through Cluster Master
  • Deploy App on Search Head Clustering
  • Load Balancing
  • Indexer Discovery
  • SOCKS Proxy

Module 14: Advanced Splunk

  • Managing Indexes
  • Manage Index Storage
  • Managing
    • Index Cluster
    • Multisite Index Cluster
  • REST API Endpoints
  • Splunk SDK

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Who should attend this Splunk Training Course?

Splunk is a leading software platform used for searching, monitoring, and analysing machine-generated Big Data. A Splunk Training Course would be beneficial to those seeking to harness this tool's capabilities for data analysis, visualisation, and operations intelligence. This course can be beneficial for a wide range of professionals, including:

  • IT Operations Professionals
  • Security Professionals
  • Data Analysts
  • Application Developers
  • System Administrators
  • Network Administrators
  • Database Administrators
  • Audit and Compliance Officers

Prerequisites of the Splunk Training Course

There are no formal prerequisites for attending this Splunk Training Course. However, a prior understanding of storing and retrieving data would be highly beneficial.

Splunk Training Course Overview

Splunk is a powerful data analytics and visualisation platform that has emerged as a crucial tool in this regard. Splunk Certifications Training Course offers comprehensive insights into Splunk's capabilities, providing a solid foundation for data professionals. Its relevance lies in enabling organisations to extract actionable insights from data, enhance security, and optimise IT operations.

Proficiency in Splunk is crucial because it equips professionals with the skills needed to manage and analyse data, and to make informed decisions efficiently. IT Administrators, Security Analysts, Data Engineers, and Business Intelligence Experts can benefit significantly from mastering Splunk. For IT professionals, it enhances troubleshooting and performance optimisation, while security experts can fortify their defences.

This intensive 2-day training by The Knowledge Academy is designed to provide a fast track to Splunk mastery. Delegates will acquire practical skills in data ingestion, visualisation, and advanced search techniques. They will learn to create dashboards, alerts, and reports, enhancing their ability to turn data into actionable insights. Additionally, participants will delve into Splunk's security and compliance features.

Course Objectives

  • To install Splunk on different platforms like macOS and Windows
  • To learn about relative-search and real-time search time modifiers
  • To acquire an understanding of filtering and reporting commands
  • To execute a chain of search commands using the pipe operator
  • To understand the use of data models and pivot in Splunk
  • To get familiar with the privileges that a user has within Splunk

After attending this training course, delegates will be able to create data models and recognise the patterns of product sales requests. They will also be able to enhance the GUI and real-time visibility in a dashboard to deliver the most up-to-date data on a wide range of performance metrics.

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What’s included in this Splunk Training Course?

  • World-Class Training Sessions from Experienced Instructors
  • Splunk Certificate
  • Digital Delegate Pack

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Not sure which course to choose?

Speak to a training expert for advice if you are unsure of what course is right for you. Give us a call on +44 1344 203999 or Enquire.

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Our training experts have compiled a range of course packages on a variety of categories in Big Data and Analytics Training, to boost your career. The packages consist of the best possible qualifications with Big Data and Analytics Training, and allows you to purchase multiple courses at a discounted rate.

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Big Data and Analytics Training FAQs

Big Data Analytics Courses teach data analysis for large datasets, including data mining, machine learning, and statistics, which is used in data-driven decision-making across various fields.
Yes, Big Data and Analytics is a rapidly growing field with high demand for skilled professionals. It offers competitive salaries, good job security, and the opportunity to work on challenging and interesting projects.
Yes, a beginner can learn Big Data. Starting with the fundamentals and gradually building expertise through our online course, tutorials, and practical experience can help beginners become proficient in this field.
Starting a career in Big Data includes learning the basics of Big Data and choosing a specific role, gaining relevant experience, creating a portfolio, and connecting with people in the Big Data field.
To succeed in Big Data and Analytics, you need skills in data analysis, programming (Python, R), knowledge of data tools (Hadoop, Spark), statistics, and domain expertise. Effective communication and problem-solving abilities are also crucial for deriving meaningful insights.
The Knowledge Academy offers Big Data and Analytics Training in a range of locations around the world, making it easy to find a training venue near you. You can also opt for our online instructor-led training sessions or self-paced training mode which allows you to complete the courses according to your timing.
Online Big Data and Analytics Training Courses offer flexibility, allowing self-paced learning without travel costs. They provide access to expert instructors and diverse resources as well.
Yes, Big Data usually requires coding.
A Big Data Analyst processes and analyses large datasets to extract insights using programming and statistical tools. Their role is essential for data-driven decision-making and in improving business operations.
Yes, Big Data Analytics is a good course choice because it provides valuable skills, high-demand job opportunities, and the ability to work with large datasets, making it a promising field for future employment.
Yes, Big Data is still in demand across multiple industries due to its valuable insights and decision-making potential. The continuous growth of data generation and its benefits to businesses ensure this demand remains strong.
The average salary for a Big Data fresher is £34,548 per year. The salary can differ due to various factors like location and experience.
The Knowledge Academy is the Leading global training provider for Big Data and Analytics Training.
The training fees for Big Data and Analytics Training in Philippines starts from $3195.
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