Why is applying a draft angle important in molding design?
Think about how parts come out of molds in real life.
Draft angles help parts release smoothly from molds, preventing damage and defects.
Given a table of faces with their draft angles, which DAX measure correctly calculates the average draft angle for all faces?
Faces = DATATABLE("FaceID", INTEGER, "DraftAngle", FLOAT, {{1, 2.5}, {2, 3.0}, {3, 1.5}})
Use the simplest function that calculates average.
AVERAGE() directly computes the mean of the DraftAngle column.
Which visualization best shows the distribution of draft angles across multiple faces in a molding design?
Think about how to show how many faces fall into different draft angle ranges.
A histogram groups draft angles into bins and shows how many faces fall into each range, making distribution clear.
You have a dataset with part IDs, face IDs, and draft angles. Which data model design best supports reporting average draft angle per part and identifying faces with draft angles below 1 degree?
Think about how to connect faces to parts for aggregation and filtering.
Two related tables allow aggregation of draft angles per part and filtering faces by draft angle easily.
Given this DAX measure to count faces with draft angle less than 1 degree, which option correctly fixes the error?
LowDraftCount = COUNTROWS(FILTER(Faces, Faces[DraftAngle] < 1))
Consider the filter context and how to remove it for correct counting.
Using ALL(Faces) removes existing filters so the measure counts all faces with draft angle less than 1.
