Summary
The reason for collecting, cleaning, and organizing data is to make it usable by the organization. One of the most common and widely used methods of access is through a business intelligence dashboard. Superset is an open source option that has been gaining popularity due to its flexibility and extensible feature set. In this episode Maxime Beauchemin discusses how data engineers can use Superset to provide self service access to data and deliver analytics. He digs into how it integrates with your data stack, how you can extend it to fit your use case, and why open source systems are a good choice for your business intelligence. If you haven’t already tried out Superset then this conversation is well worth your time. Give it a listen and then take it for a test drive today.
Announcements
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Your host is Tobias Macey and today I’m interviewing Max Beauchemin about Superset, an open source platform for data exploration, dashboards, and business intelligence
Interview
Introduction
How did you get involved in the area of data management?
Can you start by describing what Superset is?
Superset is becoming part of the reference architecture for a modern data stack. What are the factors that have contributed to its popularity over other tools such as Redash, Metabase, Looker, etc.?
Where do dashboarding and exploration tools like Superset fit in the responsibilities and workflow of a data engineer?
What are some of the challenges that Superset faces in being performant when working with large data sources?
Which data sources have you found to be the most challenging to work with?
What are some anti-patterns that users of Superset mig
