Hi @ChrisAZ ,
Thanks for the detailed information and the screenshot,it really helps clarify the issue. To fully address the duplicate entries across your “Service Task” and “Work Orders” data and enable a reliable slicer for “Reason for Repair,” I recommend creating a dimension table in Power Query. Load both source tables, select the relevant fields (“Service Task” and “Reason for Repair”), remove duplicates, append the results, and remove duplicates again to ensure you have a unique list of combinations. Name this table DimServiceTask. In the model view, create single-direction relationships from DimServiceTask[Service Task] to the corresponding “Service Task” field in each fact table (e.g., your Shop Labor tables). This avoids bi-directional filtering issues. Then, define a DAX measure like:
Total Work by Service Task =
CALCULATE(
SUMX(
VALUES(DimServiceTask[Service Task]),
CALCULATE(SUM('Shop Labor - Plastics'[Labor Cost]) + SUM('Shop Labor - Accounting'[Labor Cost]))
),
CROSSFILTER('Shop Labor - Plastics'[Service Task], DimServiceTask[Service Task], BOTH),
CROSSFILTER('Shop Labor - Accounting'[Service Task], DimServiceTask[Service Task], BOTH)
)
This ensures you are aggregating work across tables without double counting. Use DimServiceTask[Reason for Repair] in your slicer, and place DimServiceTask[Service Task] with the new measure in your visual. This will let you filter the dashboard accurately by repair reason and show the correct labor values by service task. Finally, cross-check the results with your original source data using a table visual to validate accuracy.
If my response resolve your query,consider accepting it as solution.
Regards,
Pallavi.
