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Hi guys,
I need your advice, please.
My doubt is: in terms of performances and responsiveness of PBI reports, is it better to opt for a data model design with just one (or a few) generic column(s), containing mixed but 'dense' numeric data (e.g. budget / actual values)
and then to leverage DAX expressions, creating a specific filter context for each measure, or, instead, to opt for a data model design with multiple specific numeric columns, each containing homogeneous but 'sparse' data,
pre-calculated by DB (or M) queries?
In the latter hypothesis, are null and 0s equivalent, always in terms of the engine performances, in case of summing DAX measures?
Thanks,
Alessandro
Solved! Go to Solution.
@fabiuzz ,
You may take a look at https://www.sqlbi.com/topics/optimization/.
@fabiuzz ,
You may take a look at https://www.sqlbi.com/topics/optimization/.
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