Module 1: Introduction to Azure Synapse Analytics
- Identify the business problems that Azure Synapse Analytics addresses.
- Describe core capabilities of Azure Synapse Analytics.
- Determine when to use Azure Synapse Analytics.
Module 2: Explore Azure Databricks
- Provision an Azure Databricks workspace.
- Identify core workloads and personas for Azure Databricks.
- Describe key concepts of an Azure Databricks solution.
Module 3: Introduction to Azure Data Lake storage
- Decide when you should use Azure Data Lake Storage Gen2
- Create an Azure storage account by using the Azure portal
- Compare Azure Data Lake Storage Gen2 and Azure Blob storage
- Explore the stages for processing big data by using Azure Data Lake Store
- List the supported open-source platforms
Module 4: Get started with Azure Stream Analytics
- Understand data streams.
- Understand event processing.
- Get started with Azure Stream Analytics.
Module 5: Use Azure Synapse serverless SQL pool to query files in a data lake
- Identify capabilities and use cases for serverless SQL pools in Azure Synapse Analytics
- Query CSV, JSON, and Parquet files using a serverless SQL pool
- Create external database objects in a serverless SQL pool
Module 6: Create a lake database in Azure Synapse Analytics
- Understand lake database concepts and components
- Describe database templates in Azure Synapse Analytics
- Create a lake database
Module 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
Module 8: Use Apache Spark in Azure Databricks
- Describe key elements of the Apache Spark architecture.
- Create and configure a Spark cluster.
- Describe use cases for Spark.
- Use Spark to process and analyze data stored in files.
- Use Spark to visualize data.
Module 9: Use Delta Lake in Azure Databricks
- Describe core features and capabilities of Delta Lake.
- Create and use Delta Lake tables in Azure Databricks.
- Create Spark catalog tables for Delta Lake data.
- Use Delta Lake tables for streaming data.
Module 10: Analyze data with Apache Spark in Azure Synapse Analytics
- Identify core features and capabilities of Apache Spark.
- Configure a Spark pool in Azure Synapse Analytics.
- Run code to load, analyze, and visualize data in a Spark notebook.
Module 11: Integrate SQL and Apache Spark pools in Azure Synapse Analytics
- Describe the integration methods between SQL and Spark Pools in Azure Synapse Analytics
- Understand the use-cases for SQL and Spark Pools integration
- Authenticate in Azure Synapse Analytics
- Transfer data between SQL and Spark Pool in Azure Synapse Analytics
- Authenticate between Spark and SQL Pool in Azure Synapse Analytics
- Integrate SQL and Spark Pools in Azure Synapse Analytics
- Externalize the use of Spark Pools within Azure Synapse workspace
- Transfer data outside the Synapse workspace using SQL Authentication
- Transfer data outside the Synapse workspace using the PySpark Connector
- Transform data in Apache Spark and write back to SQL Pool in Azure Synapse Analytics
Module 12: Use data loading best practices in Azure Synapse Analytics
- Understand data loading design goals
- Explain loading methods into Azure Synapse Analytics
- Manage source data files
- Manage singleton updates
- Set-up dedicated data loading accounts
- Manage concurrent access to Azure Synapse Analytics
- Implement Workload Management
- Simplify ingestion with the Copy Activity
Module 13: Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipeline
- List the data factory ingestion methods
- Describe data factory connectors
- Exercise: Use the data factory copy activity
- Exercise: Manage the self hosted integration runtime
- Exercise: Setup the Azure integration runtime
- Understand data ingestion security considerations
- Knowledge check
Module 14: Integrate data with Azure Data Factory or Azure Synapse Pipeline
- Understand Azure Data Factory
- Describe data integration patterns
- Explain the data factory process
- Understand Azure Data Factory components
- Azure Data Factory security
- Set up Azure Data Factory
- Create linked services
- Create datasets
- Create data factory activities and pipelines
- Manage integration runtime
Module 15: Perform code-free transformation at scale with Azure Data Factory or Azure Synapse Pipeline
- Explain Data Factory transformation methods
- Describe Data Factory transformation types
- Use Data Factory mapping data flow
- Debug mapping data flow
- Use Data Factory wrangling data
- Use compute transformations within Data Factory
- Integrate SQL Server Integration Services packages within Data Factory
- Knowledge check
Module 16: Orchestrate data movement and transformation in Azure Data Factory or Azure Synapse Pipeline
- Understand data factory control flow
- Work with data factory pipelines
- Debug data factory pipelines
- Add parameters to data factory components
- Integrate a Notebook within Azure Synapse Pipelines
- Execute data factory packages
- Knowledge check
Module 17: Plan hybrid transactional and analytical processing using Azure Synapse Analytics
- Describe Hybrid Transactional / Analytical Processing patterns.
- Identify Azure Synapse Link services for HTAP.
Module 18: Implement Azure Synapse Link with Azure Cosmos DB
- Configure an Azure Cosmos DB Account to use Azure Synapse Link.
- Create an analytical store enabled container.
- Create a linked service for Azure Cosmos DB.
- Analyze linked data using Spark.
- Analyze linked data using Synapse SQL.
Module 19: 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
Module 20: Configure and manage secrets in Azure Key Vault
- Explore proper usage of Azure Key Vault
- Manage access to an Azure Key Vault
- Explore certificate management with Azure Key Vault
- Configure a Hardware Security Module Key-generation solution
Module 21: Implement compliance controls for sensitive data
- Plan and implement data classification in Azure SQL Database
- Understand and configure row-level security and dynamic data masking
- Understand the usage of Microsoft Defender for SQL
- Explore how Azure SQL Database Ledger works
Module 22: Enable reliable messaging for Big Data applications using Azure Event Hubs
- Create an event hub using the Azure CLI
- Configure applications to send or receive messages through the event hub
- Evaluate performance of event hub using the Azure portal