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DoctorYSG
Helper III
Helper III

Calculated Column vs native (Performance)

I have a Fact Table of 100 Million Rows. And much much shorter Dimension Tables. THe Dimension Tables are IMPORT, and the fact table is DIRECT QUERY.

 

I understand for memory footprint and perfomance is good to minimimize column count in the Fact table. I currently have 6 colunns but I can also have only 5 if I make one of the a computed value (DAX). 

 

All tables come via a ODBC connector.

 

What is better (Pros/Cons) of:

 

A.  Using a pre-computed the 6th column  in the server, (and perhaps paying the cost of moving more data each time the DQ is done)

B. Creating a computed column in DAX in PowerBI

 

 

 

 

1 ACCEPTED SOLUTION
ppm1
Solution Sage
Solution Sage

Why are you doing DQ for the fact table? You should consider moving that to import mode, and use incremental refresh for faster refreshes. Either way, you should avoid DAX calculated columns, and move it upstream (in your data source, or in your query if you move it to import mode).

 

Pat

Microsoft Employee

View solution in original post

2 REPLIES 2
DoctorYSG
Helper III
Helper III

Good tips. But I don't want to leave your question unanswered.

 

we use DQ for two reasons. 

1. With 100 M rows, import results in going over the 10GB workspace limit.

2. The odbc connector does not work in the pbi web service. It connects to a  Palantir foundry cloud data lake, and import as well as dq are not supported yet in the to Palantir Foundry. We can use the ODBC on desktop.

 

'We are working with MSFT to setup a gateway, but our beaurocracy means that will take months.

ppm1
Solution Sage
Solution Sage

Why are you doing DQ for the fact table? You should consider moving that to import mode, and use incremental refresh for faster refreshes. Either way, you should avoid DAX calculated columns, and move it upstream (in your data source, or in your query if you move it to import mode).

 

Pat

Microsoft Employee

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