Advance your Data & AI career with 50 days of live learning, dataviz contests, hands-on challenges, study groups & certifications and more!
Get registeredGet Fabric Certified for FREE during Fabric Data Days. Don't miss your chance! Request now
Hello,
TableMain has ArrvialTime columns to lookup from 2 different tables.
Table1 key is Group and Table2 key is Category
Curretly I created columns :
Table 1 ArrivalTime and Table 2 ArrivalTime with LOOKUPVALUE and Combined arrival time
question to you, is there any more efficent way to do it please?
TableMain
| Code | Group | Category | Table 1 ArrivalTime | Table 2 ArrivalTime | Combined arrival time |
| 555 | Group1 | Category 1 | 1/1/2022 | 1/1/2022 | |
| 666 | Group1 | Category 1 | 1/1/2022 | 1/1/2022 | |
| 777 | Group2 | Category 2 | 1/1/2022 | 1/1/2022 | |
| 888 | Group2 | Category 2 | 1/1/2022 | 1/1/2022 | |
| 999 | Group4 | Category 3 | 3/3/2023 | 3/3/2023 |
Table1
| Group | ArrivalTime |
| Group2 | 1/1/2022 |
| Group3 | 3/3/2023 |
Table2
| Category | ArrivalTime |
| Category 1 | 1/1/2022 |
| Category 3 | 3/3/2023 |
Solved! Go to Solution.
@MasterSonic , Create a new column
coalesce(maxx(filter(Table1, Table1[Category] = tablemain[Category]) , Table1[ArrivalTime]) , maxx(filter(Table2, Table2[Category] = tablemain[Category]) , Table2[ArrivalTime]) )
@MasterSonic , Create a new column
coalesce(maxx(filter(Table1, Table1[Category] = tablemain[Category]) , Table1[ArrivalTime]) , maxx(filter(Table2, Table2[Category] = tablemain[Category]) , Table2[ArrivalTime]) )
you are star
Check out the November 2025 Power BI update to learn about new features.
Advance your Data & AI career with 50 days of live learning, contests, hands-on challenges, study groups & certifications and more!
| User | Count |
|---|---|
| 6 | |
| 6 | |
| 4 | |
| 4 | |
| 4 |
| User | Count |
|---|---|
| 25 | |
| 21 | |
| 10 | |
| 7 | |
| 7 |