DP-203T00 Data Engineering on Microsoft Azure

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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.

Who Should Attend

This course is ideal for data engineers, data architects, business intelligence professionals, and anyone responsible for designing or implementing data solutions in the Microsoft Azure ecosystem. Data analysts and data scientists seeking hands-on experience with Azure tools will also benefit.

Course Objectives

    After completing this course, you’ll be able to design, build, and manage end-to-end data engineering solutions on Microsoft Azure. You’ll gain practical experience in orchestrating data pipelines, transforming data for analytics, and applying best practices in security and monitoring.

    • Implement Azure data storage solutions, including Data Lake and Synapse
    • Build and manage data pipelines for batch and streaming workloads
    • Transform and analyze data using Spark and Databricks
    • Secure data environments with Azure authentication and encryption
    • Monitor, troubleshoot, and optimize data solutions for performance

Course Outline

1 - Introduction to data engineering on Azure

  • What is data engineering
  • Important data engineering concepts
  • Data engineering in Microsoft Azure

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

3 - Introduction to Azure Synapse Analytics

  • What is Azure Synapse Analytics
  • How Azure Synapse Analytics works
  • When to use Azure Synapse Analytics

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

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

6 - Create a lake database in Azure Synapse Analytics

  • Understand lake database concepts
  • Explore database templates
  • Create a lake database
  • Use a lake database

7 - Secure data and manage users in Azure Synapse serverless SQL pools

  • Choose an authentication method in Azure Synapse serverless SQL pools
  • Manage users in Azure Synapse serverless SQL pools
  • Manage user permissions in Azure Synapse serverless SQL pools

8 - Analyze data with Apache Spark in Azure Synapse Analytics

  • Get to know Apache Spark
  • Use Spark in Azure Synapse Analytics
  • Analyze data with Spark
  • Visualize data with Spark

9 - Transform data with Spark in Azure Synapse Analytics

  • Modify and save dataframes
  • Partition data files
  • Transform data with SQL

10 - 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

11 - 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

12 - 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

13 - Introduction to Azure Synapse Analytics

  • What is Azure Synapse Analytics
  • How Azure Synapse Analytics works
  • When to use Azure Synapse Analytics

14 - 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

15 - Analyze data with Apache Spark in Azure Synapse Analytics

  • Get to know Apache Spark
  • Use Spark in Azure Synapse Analytics
  • Analyze data with Spark
  • Visualize data with Spark

16 - 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

17 - Analyze data in a relational data warehouse

  • Design a data warehouse schema
  • Create data warehouse tables
  • Load data warehouse tables
  • Query a data warehouse

18 - 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

19 - Analyze data in a relational data warehouse

  • Design a data warehouse schema
  • Create data warehouse tables
  • Load data warehouse tables
  • Query a data warehouse

20 - 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 optimization

21 - Manage and monitor data warehouse activities in Azure Synapse Analytics

  • Scale compute resources in Azure Synapse Analytics
  • Pause compute in Azure Synapse Analytics
  • Manage workloads in Azure Synapse Analytics
  • Use Azure Advisor to review recommendations
  • Use dynamic management views to identify and troubleshoot query performance

22 - Secure a data warehouse in Azure Synapse Analytics

  • Understand network security options for Azure Synapse Analytics
  • Configure Conditional Access
  • Configure authentication
  • Manage authorization through column and row level security
  • Manage sensitive data with Dynamic Data Masking
  • Implement encryption in Azure Synapse Analytics

23 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics

  • Understand hybrid transactional and analytical processing patterns
  • Describe Azure Synapse Link

24 - 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

25 - 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

26 - Get started with Azure Stream Analytics

  • Understand data streams
  • Understand event processing
  • Understand window functions

27 - 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

28 - 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

29 - Explore Azure Databricks

  • Get started with Azure Databricks
  • Identify Azure Databricks workloads
  • Understand key concepts
  • Data governance using Unity Catalog and Microsoft Purview

30 - Perform data analysis with Azure Databricks

  • Ingest data with Azure Databricks
  • Data exploration tools in Azure Databricks
  • Data analysis using DataFrame APIs

31 - 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
  • Visualize data

32 - Manage data with Delta Lake

  • Get started with Delta Lake
  • Manage ACID transactions
  • Implement schema enforcement
  • Data versioning and time travel in Delta Lake
  • Data integrity with Delta Lake

33 - Build data pipelines with Delta Live Tables

  • Explore Delta Live Tables
  • Data ingestion and integration
  • Real-time processing

34 - Deploy workloads with Azure Databricks Workflows

  • What are Azure Databricks Workflows?
  • Understand key components of Azure Databricks Workflows
  • Explore the benefits of Azure Databricks Workflows
  • Deploy workloads using Azure Databricks Workflows

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