Data Engineering on Microsoft Azure DP203 Overview
Data Engineering on Microsoft Azure DP203 Course Outline
Module 1: Introduction to Data Engineering on Azure
- What Is Data Engineering?
- Important Data Engineering Concepts
- Data Engineering in Microsoft Azure
Module 2: Introduction to Azure Data Lake Storage Gen2
- Understand Azure Data Lake Storage Gen2
- Enable Azure Data Lake Storage Gen2 in Azure Storage
- Compare Azure Data Lake Store to Azure Blob Storage
- Understand the Stages for Processing Big Data
- Use Azure Data Lake Storage Gen2 in Data Analytics Workloads
Module 3: Introduction to Azure Synapse Analytics
- What is Azure Synapse Analytics?
- How Azure Synapse Analytics Works?
- When to Use Azure Synapse Analytics?
- Exercise: Explore Azure Synapse Analytics
Module 4: Use Azure Synapse Serverless SQL Pool to Query Files in a Data Lake
- Understand Azure Synapse Serverless SQL Pool Capabilities and Use Cases
- Query Files Using a Serverless SQL Pool
- Create External Database Objects
- Exercise: Query Files Using a Serverless SQL Pool
Module 5: Use Azure Synapse Serverless SQL Pools to Transform Data in a Data Lake
- Transform Data Files with the CREATE EXTERNAL TABLE AS SELECT Statement
- Encapsulate Data Transformations in a Stored Procedure
- Include a Data Transformation Stored Procedure in a Pipeline
- Exercise: Transform Files Using a Serverless SQL Pool
Module 6: Create a Lake Database in Azure Synapse Analytics
- Understand Lake Database Concepts
- Explore Database Templates
- Create a Lake Database
- Use a Lake Database
- Exercise: Analyse Data in a Lake Database
Module 7: Analyse Data with Apache Spark in Azure Synapse Analytics
- Get to Know Apache Spark
- Use Spark in Azure Synapse Analytics
- Analyse Data with Spark
- Visualise Data with Spark
- Exercise: Analyse Data with Spark
Module 8: Transform Data with Spark in Azure Synapse Analytics
- Modify and Save Dataframes
- Partition Data Files
- Transform Data with SQL
- Exercise: Transform Data with Spark in Azure Synapse Analytics
Module 9: Use Delta Lake in Azure Synapse Analytics
- Understand Delta Lake
- Create Delta Lake Tables
- Create Catalog Tables
- Use Delta Lake with Streaming Data
- Use Delta Lake in a SQL Pool
- Exercise: Use Delta Lake in Azure Synapse Analytics
Module 10: Analyse Data in a Relational Data Warehouse
- Design a Data Warehouse Schema
- Create Data Warehouse Tables
- Load Data Warehouse Tables
- Query a Data Warehouse
- Exercise: Explore a Data Warehouse
Module 11: Load Data into a Relational Data Warehouse
- Load Staging Tables
- Load Dimension Tables
- Load Time Dimension Tables
- Load Slowly Changing Dimensions
- Load Fact Tables
- Perform Post-Load Optimisation
- Exercise: Load Data into a Relational Data Warehouse
Module 12: Build a Data Pipeline in Azure Synapse Analytics
- Understand Pipelines in Azure Synapse Analytics
- Create a Pipeline in Azure Synapse Studio
- Define Data Flows
- Run a Pipeline
- Exercise: Build a Data Pipeline in Azure Synapse Analytics
Module 13: Use Spark Notebooks in an Azure Synapse Pipeline
- Understand Synapse Notebooks and Pipelines
- Use a Synapse Notebook Activity in a Pipeline
- Use Parameters in a Notebook
- Exercise: Use an Apache Spark Notebook in a Pipeline
Module 14: Plan Hybrid Transactional and Analytical Processing Using Azure Synapse Analytics
- Understand Hybrid Transactional and Analytical Processing Patterns
- Describe Azure Synapse Link
Module 15: Implement Azure Synapse Link with Azure Cosmos DB
- Enable Cosmos DB Account to Use Azure Synapse Link
- Create an Analytical Store Enabled Container
- Create a Linked Service for Cosmos DB
- Query Cosmos DB Data with Spark
- Query Cosmos DB with Synapse SQL
- Exercise: Implement Azure Synapse Link for Cosmos DB
Module 16: Implement Azure Synapse Link for SQL
- What Is Azure Synapse Link for SQL?
- Configure Azure Synapse Link for Azure SQL Database
- Configure Azure Synapse Link for SQL Server 2022
- Exercise: Implement Azure Synapse Link for SQL
Module 17: Get Started with Azure Stream Analytics
- Understand Data Streams
- Understand Event Processing
- Understand Window Functions
- Exercise: Get Started with Azure Stream Analytics
Module 18: Ingest Streaming Data Using Azure Stream Analytics and Azure Synapse Analytics
- Stream Ingestion Scenarios
- Configure Inputs and Outputs
- Define a Query to Select, Filter, and Aggregate Data
- Run a Job to Ingest Data
- Exercise: Ingest Streaming Data into Azure Synapse Analytics
Module 19: Visualize Real-Time Data with Azure Stream Analytics and Power BI
- Use a Power BI Output in Azure Stream Analytics
- Create a Query for Real-Time Visualization
- Create Real-Time Data Visualizations in Power BI
- Exercise: Create a Real-Time Data Visualization
Module 20: Introduction to Microsoft Purview
- What Is Microsoft Purview?
- How Microsoft Purview Works?
- When to Use Microsoft Purview?
Module 21: Integrate Microsoft Purview and Azure Synapse Analytics
- Catalog Azure Synapse Analytics Data Assets in Microsoft Purview
- Connect Microsoft Purview to an Azure Synapse Analytics Workspace
- Search a Purview Catalog in Synapse Studio
- Track Data Lineage in Pipelines
- Exercise: Integrate Azure Synapse Analytics and Microsoft Purview
Module 22: Explore Azure Databricks
- Get Started with Azure Databricks
- Identify Azure Databricks Workloads
- Understand Key Concepts
- Exercise: Explore Azure Databricks
Module 23: Use Apache Spark in Azure Databricks
- Get to Know Spark
- Create a Spark Cluster
- Use Spark in Notebooks
- Use Spark to Work with Data Files
- Visualise Data
- Exercise: Use Spark in Azure Databricks
Module 24: Run Azure Databricks Notebooks with Azure Data Factory
- Understand Azure Databricks Notebooks and Pipelines
- Create a Linked Service for Azure Databricks
- Use a Notebook Activity in a Pipeline
- Use Parameters in a Notebook
- Exercise: Run an Azure Databricks Notebook with Azure Data Factory
Who should attend this Data Engineering on Microsoft Azure DP203 Training Course?
The Data Engineering on Microsoft Azure DP-203 Training Course is designed for individuals who want to learn how to design and implement data solutions using Microsoft Azure's data engineering services and tools. This Microsoft Training Course can be beneficial to a wide range of professionals, including:
- Data Engineers
- Database Administrators
- Data Integration Specialists
- Data Architects
- Database Developers
- Technical Consultants
- BI (Business Intelligence) Developers
Prerequisites of the Data Engineering on Microsoft Azure DP203 Training Course
The required prerequisites for attending the Data Engineering on Microsoft Azure DP203 Training Course are to have a knowledge of cloud computing with core data concepts and professional experience with data solutions necessary and also completing AZ-900 Azure Fundamentals and DP-900 Microsoft Azure Data Fundamentals would be beneficial for the delegates.
Data Engineering on Microsoft Azure DP-203 Course Overview
This Data Engineering on Microsoft Azure DP-203 Course provides a comprehensive understanding of this vital discipline. With an emphasis on the power of Microsoft Azure, this course equips professionals with the knowledge and skills necessary to harness, process, and manage data effectively. As data becomes increasingly central to decision-making across various industries, this course serves as a gateway to harness the potential of Azure for Data Engineering solutions.
Proficiency in designing and implementing Microsoft Azure networking solutions is essential for professionals aspiring to excel in roles related to network architecture, cloud infrastructure, and IT management. This Microsoft Azure Certification Course is particularly beneficial for network engineers, cloud architects, IT managers, and system administrators. As organisations increasingly migrate to cloud-based solutions, this course becomes imperative.
The Knowledge Academy's 4-day training on Designing and Implementing Microsoft Azure Networking Solutions AZ700 offers an accelerated path to expertise in Azure networking. Delegates will engage in hands-on learning, gaining practical experience with Azure tools to design and implement effective networking solutions. This course serves as a key entry point for professionals seeking to leverage the power of Azure for networking solutions.
- To understand Azure data services and their role in Data Engineering
- To design and implement data storage solutions using Azure Data Storage Services
- To develop data processing solutions using Azure Data Factory
- To implement data transformation and data integration techniques
- To ensure data security and compliance within Azure data solutions
- To optimise and monitor data pipelines for efficiency
- To leverage Azure Databricks for Data Analytics and Machine Learning
After completing this Microsoft Azure Certification Course, delegates will gain the practical skills and knowledge to harness the power of Microsoft Azure for effective Data Engineering solutions.
What’s included in this Data Engineering on Microsoft Azure DP203 Training Course?
- World-Class Training Sessions from Experienced Instructors
- Digital Delegate Pack
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Experience live, interactive learning from home with The Knowledge Academy's Online Instructor-led Data Engineering on Microsoft Azure DP203. 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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Trainer is really very frendly and clarified all the doubts in the lab session. Assisted being with us during the labs.
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"Really good course and well organised. Trainer was great with a sense of humour - his experience allowed a free flowing course, structured to help you gain as much information & relevant experience whilst helping prepare you for the exam"
Joshua Davies, Thames Water