In this module, you will gain an understanding of data ingestion and transformation techniques. You will also learn about Transact SQL for data transformation, Azure Synapse Pipelines for ETL, Apache Spark for processing, and exploratory data analytics. The module also discusses data loading with PolyBase, the creation of data pipelines, and integration with Jupyter and Python notebooks. Additionally, it delves into configuring data snapshots with Delta Lake and building stream processing solutions using Spark Structured Streaming. Finally, you will gain a comprehensive understanding of data processing options and techniques.

In this module, you will learn about the importance of implementing robust data security measures in Azure, encompassing data encryption, access control through Azure RBAC, and secure data handling. Additionally, you can learn the steps to monitor data storage, optimize query performance through indexers and caching, and troubleshoot Spark job and pipeline run failures effectively. This knowledge is vital for maintaining efficient data storage and retrieval, contributing to improved data processing and analytics. You will also gain insight into two critical areas of Azure data management: Data security and performance optimization. You will also learn some insights on implementing robust data security measures to protect sensitive information effectively.