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.

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.

Build scalable data pipelines using Microsoft Azure tools.

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.

A core responsibility for a data engineer is to implement a data ingestion solution that loads new data into a relational data warehouse.

Data lakes are a core element of data analytics architectures. Azure Data Lake Storage Gen2 provides a scalable, secure, cloud-based solution for data lake storage.