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!