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Our org. requested that we limit the use of our data models for performance/resource management. I can create one Power BI data model through the desktop, and use separate SQL queries to import the tables. The tables are unrelated, so append/merge not an option. However, I fear that each SQL call to the same DB might be the same as having multiple data models with the single table query?
I am a novice Power BI user and have never written M statements. Is there a way to write a M query that could import all the tables? Ideally, the Power BI table names would be the same as the SQL DB names.
Solved! Go to Solution.
You won't really be saving much. You'd just have a TON of calls in one model vs a few calls in many models.
There are ways to optimize by publishing certified data sets, or using Data Flows to sync and then using those as the basis for your Power BI models. The latter might be the best, but you'd need someone to set up the right type of data flows to ensure all relevant data is published for use. Then you could have those refresh 2-3 times a day, or less if not needed more often. Then it wouldn't matter if a thousand Power BI models hit the Data Flows 7-8 times a day. Your internal server wouldn't be impacted by that.
DAX is for Analysis. Power Query is for Data Modeling
Proud to be a Super User!
MCSA: BI ReportingYou won't really be saving much. You'd just have a TON of calls in one model vs a few calls in many models.
There are ways to optimize by publishing certified data sets, or using Data Flows to sync and then using those as the basis for your Power BI models. The latter might be the best, but you'd need someone to set up the right type of data flows to ensure all relevant data is published for use. Then you could have those refresh 2-3 times a day, or less if not needed more often. Then it wouldn't matter if a thousand Power BI models hit the Data Flows 7-8 times a day. Your internal server wouldn't be impacted by that.
DAX is for Analysis. Power Query is for Data Modeling
Proud to be a Super User!
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