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We use a data vault architecture as the raw/semi-structured source for a 'traditional' data warehouse built on Snowflake. Data vault gives more advanced users access to the raw data and Snowflake gives us all the scalability we need in terms of data volume. Will of course depend on the data model in your data warehouse but works well for us.


I second the Getting to Yes recommendation. It's the best book I've found on negotiating that is actually applicable in the real world.


The latest thinking around 'data science as a product' seems to take this approach. See Building Machine Learning Powered Applications for one resource https://www.oreilly.com/library/view/building-machine-learni...


Great reference. Thanks.


I am in a similar role and have the exact same opinion. Most vendors lack flexibility, can have significant costs even for small teams, and, at the end of the day, an in-house built solution isn't that difficult.

I think it's going to be a tough road to build a sustainable business in this space.


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