3 Data Modeling Mistakes That Derail A Team

No data team is purposely trying to sabotage their own work.

But there are some common data modeling mistakes I've noticed over the years that lead to data engineers...

whether they mean to or not...

To accidentally derail their own work and effectiveness as a team.

So in this video I'm going to share three examples of some of the most common mistakes I see made as it relates to data modeling so you can hopefully avoid some of them yourself.

Or if these are things you notice already happening in your environment, you can take some steps to correct the situation before it gets too far off track.

Key Topics We'll Cover:

1. The importance of defining Facts vs Dimensions
2. The impact of granularity
3. Establishing a clear "flow" of your data

Enjoy