Which tool can help identify memory-heavy columns loaded into memory in a Direct Lake model?

• A. Vertipaq Analyzer tool
• B. Tabular Editor
• C. DAX Studio
• D. SSMS

Answer: (A)

Memory usage in a tabular model comes from how each column is stored in the in-memory engine, so to find memory-heavy columns you analyze the per-column footprint. The VertiPaq Analyzer is the dedicated tool for this task. It shows how much memory each column consumes, including data type, cardinality, compression, and encoding details, so you can pinpoint which columns are driving up the memory load when the model is loaded, such as in a Direct Lake scenario. This makes it the best fit because it is purpose-built to inspect the internal, compressed representation of columns in the VertiPaq engine, directly revealing where memory usage is highest. Other tools serve different purposes: Tabular Editor is for editing model metadata, DAX Studio focuses on writing and profiling DAX queries, and SSMS is for managing SQL Server databases—not for examining the in-memory footprint of a tabular model. Use the VertiPaq Analyzer to identify top memory consumers, then optimize by reducing cardinality, changing data types, or adjusting the model design to keep memory usage in check.