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santiagomur
Resolver II
Resolver II

PERFORMANCE

Hi, 

 

i have some issues with the performance, i create a report with many color condition and i try to engrees the speed. my principal issue is that when is loading the user can see all the infomation load (like shape, titles ) and then this shape and titles hide by the conditionals, but the employee can see that i´m hidden some think to them. (i use rls to show some info depends the role)

i`m looiking for some recomendations tips or tricks i can use before share the report. 

 

my biggest table have 181 columns but i can divede this table in 5.

1 ACCEPTED SOLUTION
v-frfei-msft
Community Support
Community Support

Hi @santiagomur ,

 

To optimize your model , Some best practices:

  • Remove unused tables or columns, where possible. 
  • Avoid distinct counts on fields with high cardinality – that is, millions of distinct values.  
  • Take steps to avoid fields with unnecessary precision and high cardinality. For example, you could split highly unique datetime values into separate columns – for example, month, year, date, and so on. Or, where possible, use rounding on high-precision fields to lower cardinality – (for example, 13.29889 -> 13.3).
  • Use integers instead of strings, where possible.
  • Be wary of DAX functions, which need to test every row in a table – for example, RANKX – in the worst case, these functions can exponentially increase run-time and memory requirements given linear increases in table size.
  • When connecting to data sources via DirectQuery, consider indexing columns that are commonly filtered or sliced again. Indexing greatly improves report responsiveness.  

 

 

Community Support Team _ Frank
If this post helps, then please consider Accept it as the solution to help the others find it more quickly.

View solution in original post

1 REPLY 1
v-frfei-msft
Community Support
Community Support

Hi @santiagomur ,

 

To optimize your model , Some best practices:

  • Remove unused tables or columns, where possible. 
  • Avoid distinct counts on fields with high cardinality – that is, millions of distinct values.  
  • Take steps to avoid fields with unnecessary precision and high cardinality. For example, you could split highly unique datetime values into separate columns – for example, month, year, date, and so on. Or, where possible, use rounding on high-precision fields to lower cardinality – (for example, 13.29889 -> 13.3).
  • Use integers instead of strings, where possible.
  • Be wary of DAX functions, which need to test every row in a table – for example, RANKX – in the worst case, these functions can exponentially increase run-time and memory requirements given linear increases in table size.
  • When connecting to data sources via DirectQuery, consider indexing columns that are commonly filtered or sliced again. Indexing greatly improves report responsiveness.  

 

 

Community Support Team _ Frank
If this post helps, then please consider Accept it as the solution to help the others find it more quickly.

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