Don't miss your chance to take the Fabric Data Engineer (DP-700) exam on us!
Learn moreNext up in the FabCon + SQLCon recap series: The roadmap for Microsoft SQL and Maximizing Developer experiences in Fabric. All sessions are available on-demand after the live show. Register now
Hello,
I'm trying to create the following table in PowerBI. It should work as following:
| Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Okt | Nov | Dec | |
| Starting Inventory | 20.000 | 25.000 | 35.000 | 25.000 | 35.000 | 40.000 | 45.000 | 55.000 | 45.000 | 25.000 | 45.000 | 35.000 |
| Production | 10.000 | 20.000 | 15.000 | 30.000 | 40.000 | 50.000 | 40.000 | 30.000 | 40.000 | 40.000 | 30.000 | 25.000 |
| Sales (forecast) | 5.000 | 10.000 | 25.000 | 20.000 | 35.000 | 45.000 | 30.000 | 40.000 | 60.000 | 20.000 | 40.000 | 30.000 |
| Closing Inventory | 25.000 | 35.000 | 25.000 | 35.000 | 40.000 | 45.000 | 55.000 | 45.000 | 25.000 | 45.000 | 35.000 | 30.000 |
| 5. Sales (forecast) per day | ||||||||||||
| 6. Days in stock (to zero) |
1. Starting inventory = StockCount[StockCount] if the month is in the past and it should be equal to the Closing Inventory for the future.
2. Production = Production[Production]
3. Sales (forecast) = Sales Actuals[sales(actuals)] if the month is in the past and it should be Sales Forecast[sales(forecast)] if the month is currently active or in the future.
4. Closing Inventory = Starting inventory + Production - Sales (forecast)
5. Sales (forecast) per day = Sales (forecast) / days of that specific month
6. Days in stock (to zero) = Starting inventory / (sales (forecast) per day that month + all months after till 0).
Example for January: 20.000 / (sales all january (5.000) + sales all february (10.000) + sales march (5.000 out of 25.000 in total).
So: 20.000 / sales jan, feb + 1/5 march
I can't share the PBIX file here yet, since I am a fairly new member. However, I can share the file by WeTransfer: https://we.tl/t-OmfofN6WoQ
Solved! Go to Solution.
first step is to fix your data model
see if you can take it from there.
first step is to fix your data model
see if you can take it from there.
Thanks for this!
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.
Share feedback directly with Fabric product managers, participate in targeted research studies and influence the Fabric roadmap.
| User | Count |
|---|---|
| 9 | |
| 6 | |
| 3 | |
| 2 | |
| 1 |
| User | Count |
|---|---|
| 21 | |
| 14 | |
| 9 | |
| 5 | |
| 5 |