Get certified for free when you join Fabric Data Days 2026 and dive into Fabric, Power BI, SQL, AI, and other essential data skills.
Join nowJuly 7 - July 17 | Round 2 of the Power BI Dataviz World Championships. Don't miss your chance! Learn more
Hello:
I am relatively new to modeling in Power BI.
I am working with a dataset that is essentially a one-stop dump for everything. Refer below:
| Qtr | Fiscal Year | Country | Category | Sub-Category | Sales |
| 1 | 2022 | A | Low | 100 | |
| 2 | 2022 | B | Med | a | 250 |
| 3 | 2023 | B | Med | b | 600 |
| 4 | 2022 | C | High | 100 | |
| 2 | 2023 | B | High | 50 | |
| 3 | 2022 | C | Low | 275 | |
| 4 | 2022 | A | Low | 210 |
Quarterly sales data for each fiscal year is being captured for 3 countries across 3 categories (only one of which has sub-categories) and is being used for dashboards. That is all that is being captured and this is expected to continue well into the future. Is this the best way to go about it? Should I be looking into breaking this table down into smaller tables? I am concerned that with more data being added over the coming years, performance is going to suffer. An suggestions/guidance would be much appreciated. Thanks in advance.
@isam2003 , One should ideally create Dimension join it back to fact
example - Distinct(Table[Country])
Qtr year table with Qtr year key or Create date from these two join with date table
Similar example
Power BI- DAX: When I asked you to create common tables: https://youtu.be/a2CrqCA9geM
https://medium.com/@amitchandak/power-bi-when-i-asked-you-to-create-common-tables-a-quick-dax-soluti...
Join us in Barcelona for FabCon and SQLCon, the Fabric, Power BI, SQL, and AI community event. Save €200 with code FABCMTY200.
Join Fabric Data Days 2026: 60 days of free live/on-demand sessions, challenges, study groups, and certification opportunities.
| User | Count |
|---|---|
| 22 | |
| 20 | |
| 17 | |
| 13 | |
| 13 |
| User | Count |
|---|---|
| 62 | |
| 40 | |
| 38 | |
| 38 | |
| 38 |