Azure Private

Data Engineering on Microsoft Azure (DP-203T00)

Course Length: 4 days

This course teaches data engineering as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies.

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Data Engineering on Microsoft Azure

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  • Private class for your team
  • Live expert instructor
  • Online or on‑location
  • Customizable agenda
  • Proposal turnaround within 1–2 business days
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Course Overview

In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.

The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure.

Course Benefits

  • Explore core data engineering concepts and the capabilities of Azure Data Lake Storage Gen2 for big data workloads.
  • Query, transform, and manage data using Azure Synapse serverless SQL pools, lake databases, and pipelines.
  • Analyze and transform data with Apache Spark and Delta Lake in Azure Synapse and Azure Databricks.
  • Design and load data into relational data warehouses and optimize their performance.
  • Implement security, authentication, and permissions in Azure Synapse Analytics.
  • Ingest and process real-time streaming data with Azure Stream Analytics and Power BI.
  • Plan and support hybrid transactional and analytical processing (HTAP) using Azure Synapse Link.

Delivery Methods

Private Class
Delivered for your team at your site or online.

Microsoft Certified Partner

Webucator is a Microsoft Certified Partner. This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).

Course Outline

  1. Introduction to data engineering on Azure
    1. What is data engineering
    2. Important data engineering concepts
    3. Data engineering in Microsoft Azure
  2. Introduction to Azure Data Lake Storage Gen2
    1. Understand Azure Data Lake Storage Gen2
    2. Enable Azure Data Lake Storage Gen2 in Azure Storage
    3. Compare Azure Data Lake Store to Azure Blob storage
    4. Understand the stages for processing big data
    5. Use Azure Data Lake Storage Gen2 in data analytics workloads
  3. Introduction to Azure Synapse Analytics
    1. What is Azure Synapse Analytics
    2. How Azure Synapse Analytics works
    3. When to use Azure Synapse Analytics
  4. Use Azure Synapse serverless SQL pool to query files in a data lake
    1. Understand Azure Synapse serverless SQL pool capabilities and use cases
    2. Query files using a serverless SQL pool
    3. Create external database objects
  5. Use Azure Synapse serverless SQL pools to transform data in a data lake
    1. Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement
    2. Encapsulate data transformations in a stored procedure
    3. Include a data transformation stored procedure in a pipeline
  6. Create a lake database in Azure Synapse Analytics
    1. Understand lake database concepts
    2. Explore database templates
    3. Create a lake database
    4. Use a lake database
  7. Secure data and manage users in Azure Synapse serverless SQL pools
    1. Choose an authentication method in Azure Synapse serverless SQL pools
    2. Manage users in Azure Synapse serverless SQL pools
    3. Manage user permissions in Azure Synapse serverless SQL pools
  8. Analyze data with Apache Spark in Azure Synapse Analytics
    1. Get to know Apache Spark
    2. Use Spark in Azure Synapse Analytics
    3. Analyze data with Spark
    4. Visualize data with Spark
  9. Transform data with Spark in Azure Synapse Analytics
    1. Modify and save dataframes
    2. Partition data files
    3. Transform data with SQL
  10. Use Delta Lake in Azure Synapse Analytics
    1. Understand Delta Lake
    2. Create Delta Lake tables
    3. Create catalog tables
    4. Use Delta Lake with streaming data
    5. Use Delta Lake in a SQL pool
  11. Build a data pipeline in Azure Synapse Analytics
    1. Understand pipelines in Azure Synapse Analytics
    2. Create a pipeline in Azure Synapse Studio
    3. Define data flows
    4. Run a pipeline
  12. Use Spark Notebooks in an Azure Synapse Pipeline
    1. Understand Synapse Notebooks and Pipelines
    2. Use a Synapse notebook activity in a pipeline
    3. Use parameters in a notebook
  13. Introduction to Azure Synapse Analytics
    1. What is Azure Synapse Analytics
    2. How Azure Synapse Analytics works
    3. When to use Azure Synapse Analytics
  14. Use Azure Synapse serverless SQL pool to query files in a data lake
    1. Understand Azure Synapse serverless SQL pool capabilities and use cases
    2. Query files using a serverless SQL pool
    3. Create external database objects
  15. Analyze data with Apache Spark in Azure Synapse Analytics
    1. Get to know Apache Spark
    2. Use Spark in Azure Synapse Analytics
    3. Analyze data with Spark
    4. Visualize data with Spark
  16. Use Delta Lake in Azure Synapse Analytics
    1. Understand Delta Lake
    2. Create Delta Lake tables
    3. Create catalog tables
    4. Use Delta Lake with streaming data
    5. Use Delta Lake in a SQL pool
  17. Analyze data in a relational data warehouse
    1. Design a data warehouse schema
    2. Create data warehouse tables
    3. Load data warehouse tables
    4. Query a data warehouse
  18. Build a data pipeline in Azure Synapse Analytics
    1. Understand pipelines in Azure Synapse Analytics
    2. Create a pipeline in Azure Synapse Studio
    3. Define data flows
    4. Run a pipeline
  19. Analyze data in a relational data warehouse
    1. Design a data warehouse schema
    2. Create data warehouse tables
    3. Load data warehouse tables
    4. Query a data warehouse
  20. Load data into a relational data warehouse
    1. Load staging tables
    2. Load dimension tables
    3. Load time dimension tables
    4. Load slowly changing dimensions
    5. Load fact tables
    6. Perform post load optimization
  21. Manage and monitor data warehouse activities in Azure Synapse Analytics
    1. Scale compute resources in Azure Synapse Analytics
    2. Pause compute in Azure Synapse Analytics
    3. Manage workloads in Azure Synapse Analytics
    4. Use Azure Advisor to review recommendations
    5. Use dynamic management views to identify and troubleshoot query performance
  22. Secure a data warehouse in Azure Synapse Analytics
    1. Understand network security options for Azure Synapse Analytics
    2. Configure Conditional Access
    3. Configure authentication
    4. Manage authorization through column and row level security
    5. Manage sensitive data with Dynamic Data Masking
    6. Implement encryption in Azure Synapse Analytics
  23. Plan hybrid transactional and analytical processing using Azure Synapse Analytics
    1. Understand hybrid transactional and analytical processing patterns
    2. Describe Azure Synapse Link
  24. Implement Azure Synapse Link with Azure Cosmos DB
    1. Enable Cosmos DB account to use Azure Synapse Link
    2. Create an analytical store enabled container
    3. Create a linked service for Cosmos DB
    4. Query Cosmos DB data with Spark
    5. Query Cosmos DB with Synapse SQL
  25. Implement Azure Synapse Link for SQL
    1. What is Azure Synapse Link for SQL?
    2. Configure Azure Synapse Link for Azure SQL Database
    3. Configure Azure Synapse Link for SQL Server 2022
  26. Get started with Azure Stream Analytics
    1. Understand data streams
    2. Understand event processing
    3. Understand window functions
  27. Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics
    1. Stream ingestion scenarios
    2. Configure inputs and outputs
    3. Define a query to select, filter, and aggregate data
    4. Run a job to ingest data
  28. Visualize real-time data with Azure Stream Analytics and Power BI
    1. Use a Power BI output in Azure Stream Analytics
    2. Create a query for real-time visualization
    3. Create real-time data visualizations in Power BI
  29. Explore Azure Databricks
    1. Get started with Azure Databricks
    2. Identify Azure Databricks workloads
    3. Understand key concepts
    4. Data governance using Unity Catalog and Microsoft Purview
  30. Perform data analysis with Azure Databricks
    1. Ingest data with Azure Databricks
    2. Data exploration tools in Azure Databricks
    3. Data analysis using DataFrame APIs
  31. Use Apache Spark in Azure Databricks
    1. Get to know Spark
    2. Create a Spark cluster
    3. Use Spark in notebooks
    4. Use Spark to work with data files
    5. Visualize data
  32. Manage data with Delta Lake
    1. Get started with Delta Lake
    2. Create Delta tables
    3. Implement schema enforcement
    4. Data versioning and time travel in Delta Lake
    5. Data integrity with Delta Lake
  33. Build Lakeflow Declarative Pipelines
    1. Explore Lakeflow Declarative Pipelines
    2. Data ingestion and integration
    3. Real-time processing
  34. Deploy workloads with Lakeflow Jobs
    1. What are Lakeflow Jobs?
    2. Understand key components of Lakeflow Jobs
    3. Explore the benefits of Lakeflow Jobs
    4. Deploy workloads using Lakeflow Jobs

Class Materials

Each student receives a comprehensive set of materials, including course notes and all class examples.

Class Prerequisites

Experience in the following is required for this Azure class:

  • Knowledge of cloud computing and core data concepts and professional experience with data solutions.
  • Comfort with basic Python and SQL.
  • Familiarity with various Azure services including Azure Synapse Analytics, Azure Stream Analytics, Azure Cosmos DB, and Azure Databricks.

Prerequisite Courses

Courses that can help you meet these prerequisites:

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