Skip to main content
cancel
Showing results for 
Search instead for 
Did you mean: 

The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now! Learn more

Reply
ericjo
Helper III
Helper III

Power BI Modeling Performance

 

Hi, I would like to ask for advice on power bi modeling.

 

ericjo_0-1752731159239.png

 

I have a table that stores by store, such as day of the week or time zone by month.
Currently, the columns keep increasing sideways according to classification like this,
and I don't know whether it would be better to increase the columns or increase the rows for use in power bi, so I'm asking.

 

The Pbix file size became too large at around 3 GB, with around 7 million rows, as the column was increased.

1 ACCEPTED SOLUTION
Ritaf1983
Super User
Super User

Hi @ericjo 

Hi,
Your current approach of using a very wide table with many columns (one for each time period or classification) introduces serious challenges:

Poor performance due to high column count and low compression

Increased file size (as you’ve already noticed)

Difficulty writing flexible DAX calculations

Complicated and fragile data model

 Recommended approach: Use a star schema.

In this structure:

You have one central Fact table with many rows and a narrow set of columns:

Store ID

Purchase Date

Product ID

Sales Amount / Quantity

Other metrics as needed

Around it, you define Dimension (Lookup) tables for:

Date (calendar)

Product

Customer

Store

Time zone, etc.

Important rule:
Each dimension table should contain one unique row per entity:

One row per product in the Product table

One row per date in the Calendar table

One row per customer in the Customer table
This ensures clean relationships and optimized performance.

This structure is the best practice for Power BI modeling, and will make your reports faster, smaller, and more maintainable.
For more guideness please relate :
https://learn.microsoft.com/en-us/power-bi/guidance/star-schema

If this post helps, then please consider Accepting it as the solution to help the other members find it more quickly.

Regards,
Rita Fainshtein | Microsoft MVP
https://www.linkedin.com/in/rita-fainshtein/
Blog : https://www.madeiradata.com/profile/ritaf/profile

View solution in original post

4 REPLIES 4
v-sdhruv
Community Support
Community Support

Hi @ericjo ,
Just wanted to check if you had a chance to review the suggesions provided?

v-sdhruv
Community Support
Community Support

Hi @ericjo ,

Just wanted to check if you had a chance to review the suggestions provided and whether that helped resolve your query?
Thank You @Ritaf1983  for your insight on the query.
Aditionally, you might want to check out  a similar post- 

https://community.fabric.microsoft.com/t5/Desktop/Performance-best-practice-with-wide-tables/m-p/280...

Hope this helps!

danextian
Super User
Super User

Hi @ericjo 

I'm wondering why your data isn't using the actual date but instead the name of days and some other  classifications. 





Dane Belarmino | Microsoft MVP | Proud to be a Super User!

Did I answer your question? Mark my post as a solution!


"Tell me and I’ll forget; show me and I may remember; involve me and I’ll understand."
Need Power BI consultation, get in touch with me on LinkedIn or hire me on UpWork.
Learn with me on YouTube @DAXJutsu or follow my page on Facebook @DAXJutsuPBI.
Ritaf1983
Super User
Super User

Hi @ericjo 

Hi,
Your current approach of using a very wide table with many columns (one for each time period or classification) introduces serious challenges:

Poor performance due to high column count and low compression

Increased file size (as you’ve already noticed)

Difficulty writing flexible DAX calculations

Complicated and fragile data model

 Recommended approach: Use a star schema.

In this structure:

You have one central Fact table with many rows and a narrow set of columns:

Store ID

Purchase Date

Product ID

Sales Amount / Quantity

Other metrics as needed

Around it, you define Dimension (Lookup) tables for:

Date (calendar)

Product

Customer

Store

Time zone, etc.

Important rule:
Each dimension table should contain one unique row per entity:

One row per product in the Product table

One row per date in the Calendar table

One row per customer in the Customer table
This ensures clean relationships and optimized performance.

This structure is the best practice for Power BI modeling, and will make your reports faster, smaller, and more maintainable.
For more guideness please relate :
https://learn.microsoft.com/en-us/power-bi/guidance/star-schema

If this post helps, then please consider Accepting it as the solution to help the other members find it more quickly.

Regards,
Rita Fainshtein | Microsoft MVP
https://www.linkedin.com/in/rita-fainshtein/
Blog : https://www.madeiradata.com/profile/ritaf/profile

Helpful resources

Announcements
Power BI DataViz World Championships

Power BI Dataviz World Championships

The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now!

December 2025 Power BI Update Carousel

Power BI Monthly Update - December 2025

Check out the December 2025 Power BI Holiday Recap!

FabCon Atlanta 2026 carousel

FabCon Atlanta 2026

Join us at FabCon Atlanta, March 16-20, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.