Everything you need to pass the Microsoft Power BI Data Analyst exam — all four objective areas explained, a 4-week study plan, the Power Query and DAX topics that decide pass/fail, and what actually appears on exam day.
Quick Summary
- • PL-300 is an Associate-level exam: 40–60 questions, ~100 minutes, 700/1000 passing score
- • Covers Power Query data prep, DAX modeling, visualization, and the Power BI service
- • Hands-on practice in Power BI Desktop matters more than reading — build a real report
- • Exam cost: $165 USD
- • No prerequisites, but it's a step up from fundamentals like PL-900 and DP-900
What is the PL-300 Exam?
The PL-300 Microsoft Power BI Data Analyst exam validates your ability to prepare, model, visualize, and analyze data with Power BI, then manage and share those assets in the Power BI service. Passing it earns the Microsoft Certified: Power BI Data Analyst Associate credential.
Unlike fundamentals exams, PL-300 tests applied skills: you connect to and clean data in Power Query, build a data model with relationships and DAX measures, design effective visuals, and configure refresh, workspaces, and row-level security. Expect scenario questions that show a model or a report requirement and ask what to do.
PL-300 is ideal for:
- • Business and data analysts who build reports in Power BI
- • Excel power users moving into Power BI
- • BI developers who want a recognized Microsoft credential
- • Anyone who finished PL-900 or DP-900 and wants the next role-based cert
| Detail | Information |
|---|---|
| Exam Code | PL-300 |
| Credential | Power BI Data Analyst Associate |
| Questions | 40–60 |
| Time Limit | ~100 minutes |
| Passing Score | 700 out of 1000 |
| Price | $165 USD |
| Level | Associate |
| Prerequisites | None (Power BI experience recommended) |
| Renewal | Annual free online assessment |
PL-300 Exam Objectives & Weightings
The PL-300 exam covers four objective areas. The first three are weighted almost equally and together account for about 80% of your score:
Objective 1: Prepare the data
25–30%- • Connect to data sources and choose import vs DirectQuery
- • Clean and transform data in Power Query Editor
- • Profile data: column quality, distribution, and statistics
- • Shape data: split/merge columns, pivot/unpivot, append and merge queries
- • Reduce model size and resolve data import errors
Objective 2: Model the data
25–30%- • Design a star schema: fact and dimension tables
- • Create and configure relationships and cardinality
- • Write DAX: calculated columns vs measures
- • Use CALCULATE, SUM, RELATED, time intelligence functions
- • Row context vs filter context; create a date table and hierarchies
Objective 3: Visualize and analyze the data
25–30%- • Choose appropriate visuals for the question
- • Format reports, bookmarks, drill-through, and tooltips
- • Configure slicers, filters, and conditional formatting
- • Add analytics: trend lines, Key influencers, decomposition tree
- • Design for accessibility and mobile layouts
Objective 4: Manage and secure Power BI
15–20%- • Create and manage workspaces and apps
- • Configure scheduled refresh and data gateways
- • Implement row-level security (RLS) roles
- • Manage datasets, endorsement, and sharing
- • Apply sensitivity labels and workspace access roles
4-Week PL-300 Study Plan
This plan assumes 1–1.5 hours of study per day with Power BI Desktop open. PL-300 rewards hands-on practice — build a real report alongside the reading, don't just watch videos.
The Most Tested PL-300 Topics
CALCULATE and Filter Context
The single most important DAX concept on the exam. CALCULATE evaluates an expression in a modified filter context. You must understand how it overrides or adds filters, and how filter context flows through relationships. Expect several questions that hinge on this.
Import vs DirectQuery vs Dual
Import loads data into the model (fast, full DAX, needs refresh). DirectQuery queries the source live (real-time, limited DAX/transforms, slower). Dual can act as either. The exam gives a requirement — data freshness, model size, source load — and asks which storage mode fits.
Relationship Cardinality and Cross-Filter Direction
One-to-many is the norm in a star schema. Many-to-many and bidirectional filtering solve specific problems but cause ambiguity and performance issues. Questions test whether you can pick the right relationship and explain a wrong total.
Calculated Columns vs Measures
Calculated columns are computed row by row at refresh and stored in the model (use for slicing/filtering). Measures are computed at query time in the current filter context (use for aggregations). Choosing wrong is a classic exam trap.
Row-Level Security (RLS)
Define roles with DAX filter expressions on tables, then assign users. Know static vs dynamic RLS (USERPRINCIPALNAME), how to test roles in Power BI Desktop, and that RLS is enforced in the service, not in Desktop viewing.
Power Query: Merge vs Append
Append stacks rows from queries with the same columns (union). Merge joins queries on a key, like a SQL join, adding columns. The exam describes a combine scenario and asks which to use and which join kind.
Ready to Practice PL-300?
500 practice questions across all four objectives, with detailed explanations. Start with 40 questions free.
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