Forum Discussion
Data Modeling and Power Query
Hi WanyaPING12 ,
Please try below things.
1. Data Modeling in Power BI: Create Relationships, If you have lookup tables (Owner Lookup), connect them via ID or Owner.
2. Avoid Calculated Columns for Large Data.
3. Use DAX Measures instead of calculated columns where possible to reduce memory usage.
4. Avoid row-by-row logic in Power Query for large datasets.
5. Consider aggregating data before loading into power bi if possible.
6. Use Dataflows if your data source is very large and shared across reports.
I hope this information helps. Please do let us know if you have any further queries.
Regards,
Dinesh
Hi WanyaPING12
- I would actually suggest sticking to the raw excel data. Import this in Powerquery and do the necessary cleaning and data type changes
- I noticed combining fields and simple if condition, all this can either be covered as calculared columns or measures else you could even build this within power query if needed upstream.
- Use matrix or table visuals to replicate Excel pivot tables using the measures or calculations you create.
The suggestion is to separate modeling and building of the actual visuals for better understanding and reusability.
Thanks for the suggestion MohamedFowzan1. Actually, I do stick to excel data but I process the Uniq Count on the excel data before loading and processing other column in the power query or table. I do have a large set of data, and the Power BI exceeds its limit, especially on row-level checking.
