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Integrating SQL and ETL Tools with Databricks

by Kishan Iyer

Databricks can be made much easier to adopt if it can be seamlessly integrated into a development environment. This course looks into how this can be accomplished for the SQL Workbench/J client and the Prophecy service.

What you'll learn

For any organization which uses Databricks, integrating this big data platform into their own tool environments can prove a complex task. In this course, Integrating SQL and ETL Tools with Databricks, you'll learn how Databricks looks into two specific tools - SQL Workbench/J and Prophecy - and links them within the Databricks workspace. First, you'll discover the need or tool integrations, how these can help engineers be more productive, and how these can avoid adding to the complexity of a tooling environment. Then, you'll explore linking an Azure Databricks workspace with a popular SQL client - namely SQL Workbench/J. Finally, you'll learn the steps involved in integrating a Prophecy workflow with Databricks. Once you complete this course, you will be well-versed with the types of integrations which are possible with Databricks, and how to link up two popular tools with this big data service.

About the author

I have a Masters in Computer Science from Columbia University and have worked previously as a developer and DevOps engineer. I now work at Loonycorn which is a studio for high-quality video content. My interests lie in the broad categories of Big Data, ML and Cloud.

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