Implement a data lakehouse analytics solution with Azure Databricks

Azure Databricks is a cloud service that provides a scalable platform for data analytics using Apache Spark.

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.

Azure Databricks is built on Apache Spark and enables data engineers and analysts to run Spark jobs to transform, analyze and visualize data at scale.

Delta Lake is a data management solution in Azure Databricks providing features including ACID transactions, schema enforcement, and time travel ensuring data consistency, integrity, and versioning capabilities.

Building data pipelines with Delta Live Tables enables real-time, scalable, and reliable data processing using Delta Lake's advanced features in Azure Databricks

Deploying workloads with Azure Databricks Workflows involves orchestrating and automating complex data processing pipelines, machine learning workflows, and analytics tasks. In this module, you learn how to deploy workloads with Databricks Workflows.