Data Engineering on Microsoft Azure

Data Engineering on Microsoft Azure (DP-203T00)

Course Length: 4 days
Delivery Methods: Multiple delivery options
Course Overview

This course teaches data professionals, data architects, and business intelligence professionals how to implement and manage data engineering workloads on Microsoft Azure. Key services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, and Azure Stream Analytics among others are utilized to perform common data engineering tasks. These tasks include 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. Additionally, data analysts and data scientists who work with analytical solutions on Microsoft Azure can also benefit from this course.

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 compute and storage options for data engineering workloads in Azure.
  • Run interactive queries using serverless SQL pools.
  • Perform data Exploration and Transformation in Azure Databricks.
  • Explore, transform, and load data into the Data Warehouse using Apache Spark.
  • Ingest and load Data into the Data Warehouse.
  • Transform Data with Azure Data Factory or Azure Synapse Pipelines.
  • Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines.
  • Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link.
  • Perform end-to-end security with Azure Synapse Analytics.
  • Perform real-time Stream Processing with Stream Analytics.
  • Create a Stream Processing Solution with Event Hubs and Azure Databricks.
Available Delivery Methods
Public Class
Public expert-led online training from the convenience of your home, office or anywhere with an internet connection. Guaranteed to run .
Private Class
Private classes are delivered for groups at your offices or a location of your choice.
Microsoft Certified Partner

Webucator is a Microsoft Certified Partner for Learning Solutions (CPLS). 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. 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
  8. Transform data with Spark in Azure Synapse Analytics
    1. Modify and save dataframes
    2. Partition data files
    3. Transform data with SQL
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. Plan hybrid transactional and analytical processing using Azure Synapse Analytics
    1. Understand hybrid transactional and analytical processing patterns
    2. Describe Azure Synapse Link
  15. 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
  16. 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
  17. Get started with Azure Stream Analytics
    1. Understand data streams
    2. Understand event processing
    3. Understand window functions
  18. 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
  19. 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
  20. Introduction to Microsoft Purview
    1. What is Microsoft Purview?
    2. How Microsoft Purview works
    3. When to use Microsoft Purview
  21. Integrate Microsoft Purview and Azure Synapse Analytics
    1. Catalog Azure Synapse Analytics data assets in Microsoft Purview
    2. Connect Microsoft Purview to an Azure Synapse Analytics workspace
    3. Search a Purview catalog in Synapse Studio
    4. Track data lineage in pipelines
  22. Explore Azure Databricks
    1. Get started with Azure Databricks
    2. Identify Azure Databricks workloads
    3. Understand key concepts
  23. 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
  24. Run Azure Databricks Notebooks with Azure Data Factory
    1. Understand Azure Databricks notebooks and pipelines
    2. Create a linked service for Azure Databricks
    3. Use a Notebook activity in a pipeline
    4. Use parameters in a notebook
Class Materials

Each student will receive a comprehensive set of materials, including course notes and all the 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.
Prerequisite Courses

Courses that can help you meet these prerequisites:

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