Learn data engineering patterns and practices as they pertain to working with batch and real-time analytical solutions using Azure data platform technologies. Begin by understanding the core compute and storage technologies that are used to build an analytical solution. Explore how to design analytical serving layers and focus on data engineering considerations for working with source files. Learn how to interactively explore data stored in files in a data lake; the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks; and how to ingest using Azure Data Factory or Azure Synapse pipelines. Grasp the various ways you can transform the data using the same technologies that is used to ingest data. Spend time learning to monitor and analyze the performance of analytical system so you can optimize the performance of data loads, or queries that are issued against the systems. Understand the importance of implementing security to ensure that the data is protected at rest or in transit. Demonstrate how you can use the data in an analytical system to create dashboards or build predictive models in Azure Synapse Analytics.
