The PL-300 exam certifies your ability to deliver business value with Microsoft Power BI, from connecting and cleaning data through modeling it with DAX, building reports, and securing the result. Its skills are measured as of April 20, 2026 across four areas: Prepare the data, Model the data, Visualize and analyze the data, and Manage and secure Power BI. Passing demands genuine fluency in Power Query for shaping data and DAX for calculations, plus a working knowledge of the Power BI Service for sharing and governance. Many questions are scenario based and reward the choice Microsoft considers best practice, such as choosing Import over DirectQuery when refresh latency allows, or using a measure instead of a calculated column. A score of 700 out of 1000 is required to pass.
What This Cheat Sheet Covers
This topic spans 19 focused tables and 199 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: Connect to Data Sources and Choose a Storage Mode
Prepare the data (25-30%) > Get or connect to data: identify and connect to data sources or a shared semantic model, change source settings (credentials and privacy levels), choose between Import, DirectQuery, and Direct Lake, and create and modify parameters.
| Concept | Example | Description |
|---|---|---|
Need fastest queries + full DAX, source small enough to copy → Import | A snapshot of the data is copied and compressed into the in-memory VertiPaq engine for fast, fully interactive visuals. • Default choice; richest feature set • Not live: needs a scheduled or manual refresh to show new source data | |
Source too big or too fast-changing to copy → DirectQuery | No data is stored; each visual sends a query to the source (DAX translated to native SQL) at report time. • Near real-time, no refresh of a copy • Limits: 1,000,000-row intermediate cap, fewer DAX features, query folding required | |
Large Fabric lakehouse, want Import speed + freshness → Direct Lake | A Fabric-only mode that reads Delta/Parquet from OneLake straight into VertiPaq; refresh is a fast metadata-only framing, not a data copy. • Not the same as DirectQuery: it uses the VertiPaq engine, not source queries • Direct Lake on SQL can fall back to DirectQuery; Direct Lake on OneLake cannot | |
Shared dimension table in a composite model → set to Dual | A table that can act as either Import or DirectQuery per query, used to cut limited relationships and speed up composite models. Returns from cache when possible, else queries the source. | |
Reuse a published, governed model → Live connection (thin report) | Connects a report to an existing published Power BI semantic model (or AAS/SSAS) with no local model built. • Always passes the user identity for security trimming • Some modeling (like calculated tables) is unavailable |