Max Talks with Databand about the Dataset Centric Approach to Data Modeling

Max was recently on the MAD Data Podcast , a podcast focused on data quality, data, ML, and AI hosted by the Databand team.

In this two part episode, Max talks about:

• IBM's acquisition of Databand
• Open source data tooling
• Data Ops and DevOps
• Why data modeling and analytics is a bit of a lost art
• Tradeoffs of Normalizing and Denormalizing
• How the dataset metaphor can help get us best of both worlds
• Datasets as a high level abstraction / interface for humans vs. what's ideal for computers at a lower level
• Shortcomings of semantic layers
• Tableau extracts as datasets?
• Entity centric visualization
• Superset supports query centric, dataset centric, and semantic centric approaches
• Does the transform layer offer enough features of semantic layer?

You can listen to both parts of Max's discussion on the podcast below!