Building and orchestrating a data pipeline for Data Lake and Spark
In this recipe, we will explore the process of constructing and orchestrating data pipelines using Data Lake and Spark in Azure Synapse Analytics. By leveraging the capabilities of these services, you can efficiently manage and process large amounts of data for analysis and insights.
We will improve the code in the notebook from the previous recipe to create a data transformation job and orchestrate it from Synapse Integrate. You’ll learn how to extract, transform, and load data into a data lake using Spark, building efficient and scalable pipelines.
Additionally, we’ll cover the crucial aspect of orchestration, where you’ll discover how to schedule, monitor, and manage the execution of your data pipelines using Azure Synapse’s orchestration capabilities.
Getting ready
To get started with the recipe, log in to your Synapse Analytics workspace. You’ll need to have the...
