Hello to everyone 🙂
Now I am wondering if there are any rules or sort of "Does and dont's" for building of data models in context of acceleration usage.
So, what I need to do is to build data model for different aggregations? f.e. amounts by customers. That's been just an example.
Due to enormous scale of events I intend to accelerate my models.
Which rules should I follow to abtain as much as possible benefits of the technology?
One more question is that how this acceleration does work. I am aware of high perfomance analytic store features but it doesn't give me an answer for the question how I can accelerate my pivots (based on data models) wich provide statistics with aggregation.
As summary, there are 2 questions:
how to build data model for pivots with figures aggregations (amount, volume, count of pieces and so on)?
how to get all benefits from such data model acceleration?
Thanks in advance 🙂
Best Regards
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