Overview of Azure Databricks

• Azure Databricks is an Apache-spark-based big data technology and analytical platform that Microsoft brought as one of its services in Azure.
• Designed with the founders of Apache-spark, Databricks is integrated with Azure to provide a one-click setup, streamlined workflows, and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts.

Features of Azure Databricks

• As Databricks is an Apache-spark-based environment, one of the key features we get is Spark SQL and dataframes which is a library that supports working with structured data which is quite similar to tables.
• Databricks also provides some services for streaming the data which helps in real-world applications and scenarios like IOT and live systems
• It also provides the advantage of Machine learning with the Spark framework itself.
• As everything is based on the Spark Core API, we have the feasibility to use the programming stack such as R, SQL, Python, Java, and Scala. It is limited to these technologies but, for data processing, this is quite enough to play around.

Imagine you are working in a sales department of a retail company. You need to analyze the data of the customers and sales to gain insights into customer behavior, product performance, and sales trends. But there is a huge amount of data to analyze, and we need such a tool that helps analyze large data and get trends of it. Microsoft Azure provides such a service which helps in processing big data and analytics purposes, Azure Databricks. This article, let us understand more about Azure data bricks and creating a Databricks workspace in Azure.