Process Data with Microsoft Azure Synapse Link for Cosmo DB

In the past, performing traditional analytical workloads with Azure Cosmos DB has been a challenge. ETL mechanisms to migrate data from Cosmos DB to platforms more suited to performing analytics on data exist, but are a challenge to develop and maintain. Azure Synapse Link for Cosmos DB addresses the needs to perform analytics over our transactional data without impacting our transactional workloads. This is made possible through the Azure Cosmos DB Analytical store, which allows us to sync our transactional data into an isolated column store without us having to develop and manage complex ETL jobs, providing us with near real-time analytical capability on our data. In this project we will step through the process of configuring the services and process data using the Microsoft Azure Synapse Link for Cosmo DB. If you enjoy this project, we recommend taking the Microsoft Azure Data Fundamentals DP-900 Exam Prep Specialization: https://www.coursera.org/specializations/microsoft-azure-dp-900-data-fundamentals

• Project Overview
• By the end of this project, you will have successfully created, and configured a Microsoft Azure Cosmos DB Database and created an analytical container. Imported sample data using a python script. Enabled Azure Synapse Link and Configured Azure Synapse Analytics to use an Apache Spark Pool to query data from the Cosmos DB database using the Azure Link and thus avoiding the management and overheads of ETL and Pipelines. You will build the environment through a series of tasks which include creating the Cosmos DB Containers and notebooks. Setting up a Synapse Workspace. Enabling Synapse linked services. Attaching to the spark pool loading and querying the Azure Cosmos DB database sample data from Azure Synapse Analytics