Migrate SQL Workloads and Data Engineering on Azure


In this course, the students will explore each stage of the data platform modernization process and define what tasks are involved at each stage, such as the assessment and planning phase. Students will also learn the available migration tools and how they are suitable for each stage of the data migration process. The students will learn how to migrate to the three target platforms for SQL based workloads: SQL Virtual Machines with RM and Azure SQL Database Managed Instances. The students will learn the benefits and limitations of each target platform and how they can be used to fulfil both business and technical requirements for modern SQL workloads.

The students will also learn about the data engineering patterns and practices as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. They will explore how to design an analytical serving layers and focus on data engineering considerations for working with source files.

Course Duration: 4 Day(s)


Explore compute and storage options for data engineering workloads

  • Introduction to Azure Storage Account
  • Describe the different Storage options in Azure Storage
  • Introduction to Azure SQL Database
  • Describe Azure SQL Database Architecture
  • Understand SQL Database hosting models
  • Introduction to Azure Synapse Analytics
  • Describe Azure Databricks
  • Introduction to Azure Data Lake storage
  • Describe Delta Lake architecture
  • Work with data streams by using Azure Stream Analytics

Plan and Implement SQL Database resources

  • Deploying SQL Server using IaaS
  • Deploying SQL Server using PaaS
    • Azure SQL Database Deployment Options o Azure SQL Database Purchasing Models

Introducing Data Platform Modernization

  • Understand Data Platform Modernization
  • Understanding the stages of migration
  • Data Migration Paths

Data Migration from on-premises SQL Server to Azure

  • Scenarios for Migration in Data Platform Modernization
  • Choosing the right tools for Migration
    • Identify Migration candidates using Data Migration Assistant
    • Evaluate a Data workload using Database Experimentation Assistant o Data Migration using Azure Database Migration Service
    • Migrate non-SQL Server workloads to Azure using SQL Migration Assistant
  • Migrating SQL Workloads to Azure Virtual Machines
  • Migrate SQL Workloads to Azure SQL Databases
  • Migrate SQL Workloads to Azure SQL Database Managed Instance

Introduction to Azure SQL Synapse Analytics for Analytical processing

  • Describe Azure SQL Synapse Analytics
  • Creating and Querying an Azure SQL Synapse Analytics

Design and implement a Modern Data Warehouse

  • Design a Modern Data Warehouse using Azure Synapse Analytics
  • Design a multidimensional schema to optimize analytical workloads

Migrate SQL Workloads and Data Engineering on Azure

  • Code-free transformation at scale with Azure Data Factory
  • Populate slowly changing dimensions in Azure Synapse Analytics pipelines

Run interactive queries using Azure Synapse Analytics serverless SQL pools

  • Explore Azure Synapse serverless SQL pools capabilities
  • Query data in the lake using Azure Synapse serverless SQL pools
  • Create metadata objects in Azure Synapse serverless SQL pools
  • Secure data and manage users in Azure Synapse serverless SQL pools

Ingest and load data into the data warehouse

  • Use data loading best practices in Azure Synapse Analytics
  • Import data with PolyBase and COPY using T-SQL
  • Petabyte-scale ingestion with Azure Data Factory
  • Perform petabyte-scale ingestion with Azure Synapse Pipelines

Transform data with Azure Data Factory or Azure Synapse Pipelines

  • Data integration with Azure Data Factory or Azure Synapse Pipelines
  • Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines
  • Create data pipeline to import poorly formatted CSV files
  • Create Mapping Data Flows

Who Should Attend

Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.

Specifically completing:

AZ-900 - Azure Fundamentals

DP-900 - Microsoft Azure Data Fundamentals


Data Engineer & Data Analyst