ETL in Azure made easy with Data Factory Data Flow

What happens when you combine a cloud orchestration service with a Spark cluster?! The answer is a feature rich, graphical, scalable data flow environment to rival any ETL tech we’ve previously had available in Azure. In this session we’ll look at Azure Data Factory v2 and how it integrates with Azure Data Bricks to produce a powerful abstraction over the Apache Spark analytics ecosystem. Now we can transform data in Azure using Data Bricks but without the need to write a single line of Scala or Python! If you haven’t used either service yet, don’t worry, you’ll get a quick introduction to both before we go deeper into the new ADF Data Flow feature.

About Paul Andrew
Paul is a Microsoft Data Platform MVP with 10+ years’ experience working with the complete on premises SQL Server stack in a variety of roles and industries. Now as Data Analytics Consultant has turned his keyboard to big data solutions on the Microsoft cloud platform. Specialising in Data Factory, Data Bricks, Data Lake and Stream Analytics. Paul is also a STEM Ambassador for the networking education in schools’ programme, PASS chapter leader, a member of the SQL Relay committee, SQL Bits, SQL Saturday, SQL Day, SQLGLA, PASS Summit speaker and helper. Currently the Stack Overflow top user for Azure Data Factory. As well as very active member of the technical community.

Email: paul@mrpaulandrew.com
Twitter: https://twitter.com/mrpaulandrew
LinkedIn: https://www.linkedin.com/in/mrpaulandrew/
Blog: https://mrpaulandrew.com/
GitHub: https://github.com/mrpaulandrew
MVP Profile: https://mvp.microsoft.com/en-us/PublicProfile/5002698