Learn how you can set up security when using Azure Synapse serverless SQL pools

Learn how to build, optimize, and maintain data pipelines for data processing and storage.

In most organizations, a data engineer is the primary role responsible for integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions. An Azure data engineer also helps ensure that data pipelines and data stores are high-performing, efficient, organized, and reliable, given a specific set of business requirements and constraints.

Learn how to perform data analysis using Azure Databricks. Explore various data ingestion methods and how to integrate data from sources like Azure Data Lake and Azure SQL Database. This module guides you through using collaborative notebooks to perform exploratory data analysis (EDA), so you can visualize, manipulate, and examine data to uncover patterns, anomalies, and correlations.

Data engineers commonly need to transform large volumes of data. Apache Spark pools in Azure Synapse Analytics provide a distributed processing platform that they can use to accomplish this goal.

With Azure Synapse serverless SQL pool, you can leverage your SQL skills to explore and analyze data in files, without the need to load the data into a relational database.