Which of the following best describes the primary purpose of a Bill of Materials (BOM) in SolidWorks?
Think about what information you need to order parts and build a product.
A BOM lists all parts and subassemblies with quantities and identifiers needed to build the product. It is essential for procurement and manufacturing.
Given a BOM table with columns PartID, QuantityPerAssembly, and AssemblyCount, which DAX measure correctly calculates the total quantity of each part needed for all assemblies?
Multiply the quantity per assembly by how many assemblies are needed, then sum for all parts.
Option D correctly multiplies quantity per assembly by assembly count for each row, then sums all results to get total quantities.
You want to visualize the hierarchical structure of a BOM showing assemblies and their subassemblies with quantities. Which visualization type is best suited for this in a BI dashboard?
Think about how to show parent-child relationships clearly with quantities.
A tree map visually represents hierarchical data well, showing assemblies and subassemblies with area size indicating quantity, making it easy to understand structure and volume.
Given this DAX measure to calculate total part quantity:TotalQty = SUM(BOM[QuantityPerAssembly] * BOM[AssemblyCount])
Why does this measure return an error?
Consider how SUM works with column operations in DAX.
SUM expects a single column, but multiplying two columns directly inside SUM is invalid. SUMX iterates row by row allowing multiplication per row.
You manage a BOM with thousands of parts and multiple assembly levels. Performance is slow when calculating total quantities and generating reports. Which data modeling approach best improves performance?
Think about how BI tools handle large datasets efficiently.
A star schema with fact and dimension tables and surrogate keys reduces data redundancy and improves query performance for large BOMs.
