CompTIA Data+ Course Outline

Module 1: Identifying Basic Concepts of Data Schemas

  • Identify the Key Differences Between Relational and Non-Relational Databases
    • Relational Databases
    • Non-Relational Databases

Lab: Navigating and Understanding Database Design

  • Identify the Way We Use Tables, Primary Keys, and Normalisation
    • Normalisation
    • Normalising Data
    • Relationships in Data
    • Types of Relationships
    • Referential Integrity
    • Denormalisation

Module 2: Understanding Different Data Systems

  • Describe Types of Data Processing and Storage Systems
    • Types of Data Processing
    • Source Systems
    • Data Warehouses and Data Marts
    • Schemas Used in Data Warehousing
    • Fact Table
    • Dimension Table
    • Star Schema
    • Snowflake Schema
    • Data Lakes and Lakehouses
  • Explain How Data Changes
    • Overview of Slowly Changing Dimensions
    • Impact of Slowly Changing Dimensions

Module 3: Understanding Data Types and Characteristics of Data

  • Understand Types of Data
    • Quantitative Data
    • Qualitative Data
    • Why do the Data Types Matter?
  • Break Down the Field Data Types
    • Introduction to Field Data Types
    • Text/Alphanumeric Field Data Types
    • Date Data Type
    • Number Date Types
    • Currency Data Type
    • Boolean Data Type
    • Data Type Conversion

Lab: Understanding Data Types and Conversion

Lab: Understanding Data Structure and Types and Using Basic Statements

Module 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages

  • Differentiate Between Structured Data and Unstructured Data
    • Structured Data
    • Unstructured Data
  • Recognise Different File Formats
    • Delimited Files
    • Why We Use Delimited Files?
    • Flat Files
    • File Extensions

Lab: Working with Different File Formats

  • Understand the Different Code Languages Used for Data
    • Structured Query Language (SQL)
    • Structured Hyper Text Markup Language (HTML)
    • Extensible Markup Language (XML)
    • JavaScript Object Notation (JSON)

Module 5: Explaining Data Integration and Collection Methods

  • Understand the Processes of Extracting, Transforming, and Loading Data
    • Extracting Data
    • Transforming Data
    • Loading Data
    • Full Load and Delta Load
    • Extract, Load, Transform (ELT)
  • Explain API/Web Scraping and Other Collection Methods
    • Application Programming Interface (API)
    • Web Services
    • Web Scraping
    • Machine Data
  • Collect and Use Public Data
    • Overview of Public and Publicly-Available Data
    • Finding Public and Publicly-Available Data

Lab: Using Public Data

  • Use and Collect Survey Data
    • Considerations for Using Surveys
    • Question Design
    • Types of Survey Answers

Module 6: Identifying Common Reasons for Data Cleansing and Profiling Datasets

  • Learn to Profile Data
    • Steps of Data Profiling
    • Data Profiling Tools and Techniques

Lab: Profiling Data Sets

  • Address Redundant and Duplicated Data
    • Redundant Data
    • Duplicated Data
    • Unnecessary Fields

Lab: Addressing Redundant and Duplicated Data

  • Work with Missing Values
    • Causes of Null Values
    • Filtering Null Values
    • Replacing Missing Values

Lab: Addressing Missing Values

  • Address Invalid Data
    • Identifying Invalid Data
    • Removing Invalid Data
    • Replacing Invalid Data with Valid Data
  • Convert Data to Meet Specifications
    • Data That Does Not Meet Specifications
    • Converting Data Types

Lab: Preparing Data for Use

Module 7: Executing Different Data Manipulation Techniques

  • Recode Data and Derived Variables
    • Recoding Numerical and Categorical Data
    • Derived Variables
    • Imputing Values
    • Reduction in Data Sets
    • Masking Values

Lab: Recoding Data

  • Transpose and Append Data
    • Transposing Data
    • Appending Data
  • Query Data
    • Querying Data
    • Types of Joins

Lab: Working with Queries and Join Types

Module 8: Explain Common Techniques for Data Manipulation and Optimisation

  • Use Functions to Manipulate Data
    • Text Functions
    • Text Functions - Left, Right, Mid
    • Text Functions - Upper, Lower, and Proper
    • Combining Data Fields
    • Parsing Strings for Information
    • Date Functions
    • Logical Functions and Conditional Formatting
    • Aggregation and the Basic Types of Aggregate Functions
    • System Functions
  • Use Common Techniques for Query Optimisation
    • Filtering Data
    • Parameterisation
    • Indexing Data
    • Temporary Tables
    • Sub Querying and Subsets of Information
    • Query Execution Plan

Lab: Building Queries and Transforming Data

Module 9: Applying Descriptive Statistical Methods

  • Use Measures of Central Tendency
    • Measures of Central Tendency Overview
    • Mean
    • Median
    • Mode

Lab: Using the Measures of Central Tendency

  • Use Measures of Dispersion
    • Overview of the Measures of Dispersion
    • Range of Data
    • Standard Deviation
    • Z-Scores
    • Distribution of a Data Set

Lab: Using the Measures of Variability

  • Use Frequencies and Percentages
    • Frequency
    • Percentage Difference
    • Percentage Change

Module 10: Describing Key Analysis Techniques

  • Get Started with Analysis
    • Research Questions
    • Sample Research Questions
    • Data Sources and Collection Methods
    • Observations
  • Recognise Types of Analyses
    • Exploratory Analysis
    • Performance Analysis
    • Gap Analysis
    • Trend Analysis
    • Link Analysis

Module 11: Understanding the Use of Different Statistical Methods

  • Understand the Importance of Statistical Tests
    • Confidence Intervals
    • T-Tests and P-Values
  • Break Down the Hypothesis Test
    • Null Hypothesis
    • Understanding the Results of Hypothesis Testing
  • Understand Tests and Methods to Determine Relationships Between Variables
    • Chi-Square
    • Chi-Square Tests
    • Simple Linear Regression
    • Correlation
    • Use Excel to Apply Statistical Methods

Lab: Analysing Data

Module 12: Using the Appropriate Type of Visualisation

  • Use Basic Visuals
    • Pie Chart
    • Treemaps
    • Column and Bar Charts
    • Line Graphs

Lab: Building Basic Visuals to Make Visual Impact

  • Build Advanced Visuals
    • Stacked Column/Bar Charts
    • Line Graphs with Multiple Lines
    • Combination Charts
    • Scatter Plots
    • Bubble Charts
    • Histograms
    • Waterfall Charts
  • Build Maps with Geographical Data
    • Preparing Geo Fields for Mapping
    • Geographic Maps

Lab: Building Maps with Geographical Data

  • Use Visuals to Tell a Story
    • Heat Maps
    • Word Clouds
    • Infographics

Lab: Using Visuals to Tell a Story

Module 13: Expressing Business Requirements in a Report Format

  • Consider Audience Needs When Developing a Report
    • Audience
    • Consumer Types
  • Describe Data Source Considerations for Reporting
    • Documenting the Source Data
    • Determining Access to Data
    • Developing Views of the Data
    • Data Fields and Attributes
  • Describe Considerations for Delivering Reports and Dashboards
    • Determining How Visuals Will Be Viewed
    • Determining How Data Will Be Delivered
    • Frequency of Reporting
    • Recurring Reports
  • Develop Reports or Dashboards
    • Visualisation Layouts
    • Mock-up and Wireframing for Design
    • Types of Visuals
    • Types of Dashboard Navigation
  • Understand Ways to Sort and Filter Data
    • Sorting Data
    • Filter Methods for Visuals
    • Filtering by Date Ranges

Lab: Filtering Data

Module 14: Designing Components for Reports and Dashboards

  • Design Elements for Reports/Dashboards
    • Branding Guidelines
    • Appropriate Colour Schemes
    • Appropriate Fonts and Layout
    • Naming Conventions

Lab: Designing Elements for Dashboards

  • Utilise Standard Elements
    • Standard Information and Formatting Elements for Reports
    • Other Special Fields
    • Watermarks
    • Important Dates
  • Create a Narrative and Other Written Elements
    • Narrative
    • Instructions for Using the Report/Dashboard
    • Other Supporting Materials
  • Understand Deployment Considerations
    • Techniques for Dashboard Optimisation
    • Expand and Collapse Options for Information
    • Drill Through
    • Tooltips
    • Other Considerations
    • Deploy to Production

Module 15: Distinguish Different Report Types

  • Understand How Updates and Timing Affect Reporting
    • Static Vs Dynamic Reports
    • Point-in-Time Reporting
    • Real-Time Reporting
  • Differentiate Between Types of Reports
    • Operational and Compliance Reports
    • Tactical and Research-Driven Reporting
    • Ad-Hoc Reporting
    • Self-Service Reporting

Lab: Building an Ad Hoc Report

Lab: Visualising Data

Module 16: Summarising the Importance of Data Governance

  • Define Data Governance
    • Lifecycle of Data
    • Roles Within a Data Governance Team
    • Jurisdiction Requirements
    • Regulations and Compliance
    • Data Classifications
  • Understanding Access Requirements and Policies
    • Data Use Agreements
    • Release Approvals
    • Data Retention and Destruction Policies
  • Understand Security Requirements
    • Data Processing
    • Data Transmission
    • Data Encryption
    • De-Identification and Masking of Data
    • Data Breaches
    • Data Access
    • Saving Data Files and Storage Types

Lab: Building Basic Visuals to Make Visual Impact

  • Understanding Entity Relationship Requirements
    • Entity Relationship Models
    • Record Linkage Restrictions
    • Data Constraints

Module 17: Applying Quality Control to Data

  • Describe Characteristics, Rules, and Metrics of Data Quality
    • Reasons to Check Data Quality
    • Understanding Quality
    • Rules and Metrics for Data Quality
  • Identify Reasons to Quality Check Data and Methods of Data Validation
    • Data Validation Methods
    • Automated Validation
    • Data Verification Methods

Module 18: Explaining Master Data Management

  • Explain the Basics of Master Data Management
    • Master Data Management
    • Benefits of Master Data Management
    • Reasons for Master Data Management
    • Master Data Management Vs Data Warehouse
  • Describe Master Data Management Processes
    • Consolidation of Multiple Data Fields
    • Field Standardisation
    • Data Dictionary
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Who should attend this CompTIA Data+ Course?

The CompTIA Data+ Course is a vendor-neutral certification that validates the knowledge and skills required to manage data in a variety of environments. It is designed for IT professionals who are responsible for collecting, storing, processing, and analysing data. This course can be beneficial for various professionals including:

  • Data Analysts
  • Database Administrators
  • Data Engineers
  • Business Analyst
  • Entry-level Data Scientists
  • Systems Analysts
  • IT Managers
  • Data Consultants

Prerequisites of the CompTIA Data+ Course

There are no formal prerequisites to attend the CompTIA Data+ Course, but to be eligible for the certification exam, you must have a minimum of 18-24 months of experience in a report/business analyst role, be familiar with databases and analytics tools, possess a foundational knowledge of statistics, and have experience in data visualisation.

CompTIA Data+ Course Overview

The CompTIA Data+ Certification offers a comprehensive introduction to data analytics, a critical skill in today’s data-driven business landscape. As organisations increasingly rely on data to make informed decisions, understanding data management, visualisation, and reporting has become essential. CompTIA Data+ Certification Training equips delegates with foundational knowledge to handle data effectively, making it an invaluable asset for professionals in various fields.

Proficiency in Data Analytics is crucial for professionals involved in Business Intelligence, Market Research, Operations, and any role that requires data-driven decision-making. Gaining expertise in this area enables professionals to analyse complex data sets, identify trends, and provide actionable insights, ultimately leading to better business outcomes. Therefore, mastering these skills is essential for anyone looking to advance in a data-centric role.

This 2-day training offered by The Knowledge Academy is designed to provide delegates with a solid understanding of the key concepts and tools used in data analytics. Delegates will learn how to collect, analyse, and interpret data effectively through hands-on exercises and real-world examples. CompTIA Data+ Certification Training will help delegates enhance their analytical skills, enabling them to add value to their organisations by leveraging data for strategic decision-making.

CompTIA Data+ Course Objectives

  • To understand the importance of data analytics in modern business
  • To learn the basics of data management and storage
  • To explore data visualisation techniques
  • To gain proficiency in data reporting and interpretation
  • To develop skills in data-driven decision-making
  • To enhance problem-solving capabilities using data

After completing the course, delegates will be well-prepared for the CompTIA Data+ Certification exam, demonstrating their proficiency in data analytics. This certification will validate their skills and knowledge, opening up new career opportunities and advancement in the field of data analysis.

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What’s included in this CompTIA Data+ Course?

  • World-Class Training Sessions from Experienced Instructors
  • CompTIA Data+ Certificate
  • Digital Delegate Pack
Hands-On Labs: Included as part of our online instructor-led delivery, these labs provide real-world exercises in a simulated environment guided by expert instructors to enhance your practical skills.
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Toronto, a city in the Canadian province of Ontario, has an average population of roughly 2,615,000 spread across 243.33 square miles of land – making it the busiest and most populous region in the whole of Canada.  At The Knowledge Academy, we offer 50,000 classroom based training courses throughout the different areas of Toronto, in order to enhance people’s learning in an array of subject areas.  Education in Canada is generally funded by federal, provincial, and local governments; the system is divided into primary, secondary and post-secondary education and is operated under provincial jurisdiction.  On the whole, there are 190 days in a school year, starting in September and ending towards the last Friday of June.  Some popular and highly regarded universities in Canada include: the University of Toronto (notable alumni including: William Lyon Mackenzie King, Vincent Massey, Donald Sutherland and Lesra Martin), the University of British Columbia (notable alumni including: Eddie Peng, Justin Trudeau and Nardwuar the Human Serviette), and the University of Alberta (notable alumni including: Dayo Wong, George Stanley and Beverley McLachlin).  With its massively diverse citizenry and education options, it is hard to solely categorise the formation of its education system; it is also the home site to four publicly funded K12 school boards, a publicly funded religious K12 school board, a range of K12 private and prepatory school and a plethora of other religious, vocational, career and specialist schools.  As French is a commonly spoken language in Canada, there are also a number of public school boards designed for French language students.  Regarding religious schools, there are a number of Christian, Islamic and Jewish schools based in Toronto, all of which offering a slightly different educational system to their students and are tailored to best suit a specific religion.  With non-public schooling in mind, there are also a variety of religious non-public school boards spread throughout Toronto, namely the Board of Jewish Education of Toronto and the Toronto Adventist District School Board.  

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Experience live, interactive learning from home with The Knowledge Academy's Online Instructor-led CompTIA Data+ Course Course. Engage directly with expert instructors, mirroring the classroom schedule for a comprehensive learning journey. Enjoy the convenience of virtual learning without compromising on the quality of interaction.

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Package deals for CompTIA Data+ Course

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CompTIA Data+ Course | CompTIA Training in Toronto FAQs

What is CompTIA?

CompTIA is a globally recognised non-profit organisation that offers vendor-neutral IT certifications, helping professionals validate skills in areas like cybersecurity, cloud, data analytics, networking, and IT support.

What are the prerequisites for taking this CompTIA Data+ Course?

There are no formal prerequisites, but it’s recommended to have 18–24 months’ experience in a reporting or analyst role, with knowledge of databases, statistics, analytics tools, and data visualisation for the CompTIA Data+ Certification exam.

Who should attend this CompTIA Data+ Training?

CompTIA Data+ Certification Training is ideal for professionals in data roles such as Analysts, Business Intelligence Specialists, and individuals transitioning into data-centric positions in IT or business functions.

What kind of skills will I gain after completing this course?

You’ll gain skills in data mining, analysis, visualisation, governance, and reporting. These are critical for transforming data into meaningful business insights and supporting data-driven decision-making.

What is included in CompTIA Data+ Certification?

In this CompTIA Data+ Certification, delegates will have intensive training with our experienced instructors, a digital delegate pack consisting of important notes related to this course, and a certificate after course completion.

What will I learn in this course?

You’ll learn data concepts, environments, mining techniques, data visualisation, governance, quality control, and how to interpret results to support business objectives and operational strategies.

What is the duration of the CompTIA Data+ Training?

This course takes 2-day to complete during which delegates participate in intensive learning sessions that cover various course topics.

How long is the CompTIA Data+ Certification valid for?

CompTIA Data+ Certification is valid for three years. You can maintain its validity through continuing education activities or by earning a higher-level CompTIA certification.

How to renew the CompTIA Data+ Certification?

You can renew the certification by completing CompTIA’s Continuing Education (CE) programme, which includes activities like attending webinars, taking courses, or passing another qualifying certification.

Do you offer 24/7 support for this CompTIA Data+ Training?

Yes, The Knowledge Academy offers 24/7 support via phone & email before attending, during, and after the course. Our customer support team is available to assist and promptly resolve any issues you may encounter.

Who should I contact if I am unable to access my course?

If you are unable to access your CompTIA Data+ Certification Training , contact the support team at The Knowledge Academy via their customer service email or phone number provided on their website for prompt assistance and resolution of your issue.

How does CompTIA Data+ Certification differ from other Data Analytics Certifications?

CompTIA Data+ is vendor-neutral, focusing on foundational analytics, governance, and reporting. It’s ideal for early-career professionals and differs from advanced, tool-specific certifications like Microsoft or Tableau.

Will I receive a certification after completing this course?

Yes, after completing this course you will receive a certificate of completion to validate your achievement and demonstrate your proficiency in the course material.

Do you provide self-paced learning for this CompTIA Data+ Certification?

Yes, The Knowledge Academy provides flexible self-paced option for the CompTIA Data+ Certification Training. Self-paced training is beneficial for individuals who have an independent learning style and wish to study at their own pace and convenience.

How will this CompTIA Data+ Training benefit my career?

The CompTIA Data+ Certification Training validates essential data skills, improves job readiness, and opens up opportunities in data-driven roles, enhancing your credibility and confidence in analytics environments.

What career opportunities are available to individuals who have earned the CompTIA Data+ Certification?

Career paths include Data Analyst, Business Analyst, Reporting Analyst, Database Technician, and other roles where data handling, interpretation, and presentation are critical.

In what ways can this course enhance my career prospects in the data industry?

The course builds a strong foundation in analytics, enabling you to transition into more technical or specialised data roles and stay relevant in a growing data-driven industry.

How does the CompTIA Data+ Course stay aligned with current industry trends and employer demands?

CompTIA Data+ is regularly updated based on industry research and employer feedback, ensuring the content reflects current data roles, technologies, and compliance practices relevant to real-world workplace demands.

Will the CompTIA Data+ Course help me understand strategies for scaling a data-driven business?

Yes, the course introduces concepts like data lifecycle management and governance that support scalable data practices, helping you contribute to smarter decision-making as organisations grow.

How will the CompTIA Data+ course strengthen my ability to innovate and contribute to data initiatives within my organisation?

The course sharpens your analytical thinking, data interpretation, and reporting skills-enabling you to support and drive innovative, insight-led initiatives aligned with business goals.

Why choose The Knowledge Academy over others?

The Knowledge Academy in Toronto stands out as a prestigious training provider known for its extensive course offerings, expert instructors, adaptable learning formats, and industry recognition. It's a dependable option for those seeking this course.

What is the cost/training fees for CompTIA Data+ Course in Toronto?

The training fees for CompTIA Data+ Coursein Toronto starts from CAD4295

Which is the best training institute/provider of CompTIA Data+ Course in Toronto?

The Knowledge Academy is the Leading global training provider for CompTIA Data+ Course.

What are the best CompTIA Certification Training Courses courses in Toronto?

Please see our CompTIA Certification Training Courses courses available in Toronto

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