| Id | Name | Description | Useful links |
|---|---|---|---|
| Lab 01 | The Integrated Machine Learning process in Synapse Analytics | This lab demonstrates the integrated, end-to-end Azure Machine Learning and Azure Cognitive Services experience in Azure Synapse Analytics. You will learn how to connect an Azure Synapse Analytics workspace to an Azure Machine Learning workspace using a Linked Service and then trigger an Automated ML experiment that uses data from a Spark table. You will also learn how to use trained models from Azure Machine Learning or Azure Cognitive Services to enrich data in a SQL pool table and then serve prediction results using Power BI. After completing the lab, you will understand the main steps of an end-to-end Machine Learning process that build on top of the integration between Azure Synapse Analytics and Azure Machine Learning. |
https://docs.microsoft.com/en-us/azure/synapse-analytics/machine-learning/quickstart-integrate-azure-machine-learning https://docs.microsoft.com/en-us/azure/synapse-analytics/machine-learning/tutorial-sql-pool-model-scoring-wizard |
| Lab 02 | Working with Apache Spark in Synapse Analytics | This lab demonstrates the experience of working with Apache Spark in Azure Synapse Analytics. You will learn how to connect an Azure Synapse Analytics workspace to an Azure Data Explorer workspace using a Linked Service and then load data from one of its databases using a Spark notebook. You will also learn how to use libraries like Hyperspace and MSSparkUtil to optimize the experience of working with Data Lake storage accounts from Spark notebooks. In addition to Data Explorer and Data Lake storage, the data enrichment process will also use historical data from a SQL Pool. In the end, you will learn how to publish the enriched data back into the Data Lake and consume it with the SQL Built-in Pool and Power BI. After completing the lab, you will understand the main steps of an end-to-end data enrichment process that uses Spark in an Azure Synapse Analytics workspace. |
https://docs.microsoft.com/en-us/azure/synapse-analytics/spark/apache-spark-overview https://techcommunity.microsoft.com/t5/azure-data-explorer/announcing-azure-data-explorer-data-connector-for-azure-synapse/ba-p/1743868 |
| Lab 03 | Migrating Data Factory Pipelines to Synapse Analytics Pipelines | This lab demonstrates the experience of migrating an existing Azure Data Factory pipeline to an Azure Synapse Analytics Pipeline. You will learn how to script major ADF artifacts like linked services, datasets, activities, and pipelines. You will also learn how to import these artifacts into Azure Synapse Analytics. In the end, you will learn to validate, test, and trigger the imported Azure Synapse Pipeline. After completing the lab, you will understand the main steps of a migration process from Azure Data Factory pipelines to Azure Synapse Analytics pipelines. |
https://docs.microsoft.com/en-us/dotnet/api/azure.analytics.synapse.artifacts?view=azure-dotnet-preview |
| Lab 04 | Working with the Common Data Model in Synapse Analytics | This lab demonstrates using Synapse Analytics Spark to work with the Common Data Model. | https://docs.microsoft.com/en-us/common-data-model/ |
| Name | Description |
|---|---|
| Adding an Azure Synapse Analytics workspace to an existing Azure SQL Data Warehouse instance | This video provides an overview on how to add an Azure Synapse Analytics workspace on top of an existing Azure Synapse Analytics (formerly SQL DW) instance. |
| Azure Synapse Analytics Git integration and workspace management | This video provides an overview of the new Git integration features in Synapse Analytics as well as some of other features related to workspace management (folders and worskpace access control). |
| Azure Synapse Analytics monitoring | This video provides an overview of the new monitoring capabilities in Synapse Analytics. It covers Az Monitor integration as well as SQL and Spark pool monitoring. |
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