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

Srini Kadamati

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!

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