In this challenge, you will optimize a batch processing solution by using Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake. First, you will create a storage account that uses a Data Lake Storage hierarchical namespace, and then you will design a batch processing solution. Next, you will run a performance benchmark to optimize and ingest data for a data lake by using the AzCopy utility, and then you will deploy an Azure data factory that contains a data pipeline to transform data into a blob data file. Finally, you will create a data pipeline in Azure Synapse Studio to populate a new, dedicated SQL pool, and then you will create a data pipeline to run a performance benchmark by using a data factory. Note: Once you begin the challenge lab, you will not be able to pause, save, or return to your challenge lab. Please ensure that you have set aside enough time to complete the challenge lab before you start.
Learning Objectives
In this challenge, you will optimize a batch processing solution by using Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake. First, you will create a storage account that uses a Data Lake Storage hierarchical namespace, and then you will design a batch processing solution. Next, you will run a performance benchmark to optimize and ingest data for a data lake by using the AzCopy utility, and then you will deploy an Azure data factory that contains a data pipeline to transform data into a blob data file. Finally, you will create a data pipeline in Azure Synapse Studio to populate a new, dedicated SQL pool, and then you will create a data pipeline to run a performance benchmark by using a data factory. Note: Once you begin the challenge lab, you will not be able to pause, save, or return to your challenge lab. Please ensure that you have set aside enough time to complete the challenge lab before you start.