ExamSprintLab

PL-300 study plan: pass in 4 weeks

Updated October 9, 2026

Four weeks is realistic for PL-300 if you already open Power BI Desktop at work and can study 8–10 hours a week. The plan follows the exam’s own loop: prepare the data in week 1, model it in week 2, visualise it in week 3, and manage and secure it in week 4, with a practice-test review at the end. Without any experience of Power BI, double the timeline, and spend the extra time on weeks 1 and 2.

Before you start

  • Read the official skills outline once. It is short and lists every objective.
  • Install Power BI Desktop, which is free, and sign in to the Power BI service with a work or school account or a developer or trial licence. Several week 4 topics, such as workspaces, apps and row-level security membership, only exist in the service.
  • Pick one realistic dataset with a fact table and a few dimensions: sales orders, products, customers, dates. Build every week’s work on the same project.
  • Take the free Microsoft practice assessment cold. The score does not matter yet; the per-domain breakdown does.

Week 1: prepare the data (25–30%)

Goal: get messy data into clean, well-typed tables.

  • Connect: choose a source, change credentials and privacy levels, understand Import versus DirectQuery versus Direct Lake, and create parameters.
  • Profile: column quality, column distribution and column profile; know that profiling uses the top 1000 rows unless you change it.
  • Clean: replace values, fix data types, handle nulls and errors, and resolve import errors.
  • Shape: group by, pivot, unpivot and transpose; split and extract columns; convert JSON or XML into a table.
  • Combine: merge (joins, columns) versus append (stacks, rows); reference versus duplicate queries.
  • Design: split a flat file into fact and dimension tables, and create keys for relationships.

Project: load two CSV or Excel files with deliberate problems (text numbers, nulls, duplicates). Produce one fact and two dimension queries, with the source path held in a parameter.

Week 2: model the data (25–30%)

Goal: a star schema with measures you can explain line by line.

  • Relationships: cardinality, cross-filter direction, active versus inactive, role-playing dimensions with USERELATIONSHIP.
  • Date table: create a contiguous calendar, mark it as a date table, and understand why time intelligence needs it.
  • DAX basics: measures versus calculated columns, filter context and row context, CALCULATE with filters, ALL and ALLSELECTED, DIVIDE, and iterators.
  • Time intelligence: TOTALYTD, DATESYTD, SAMEPERIODLASTYEAR, DATEADD.
  • More DAX: semi-additive measures, quick measures, calculation groups, and basic statistical functions.
  • Performance: remove unused rows and columns, reduce granularity, use Performance Analyzer and DAX query view.

Project: build five measures, among them total sales, sales last year, year-to-date, percent of all products and a closing-balance measure. Then break each one by putting it in a matrix and explaining every number.

Week 3: visualize and analyze (25–30%)

Goal: a report someone else can use without help.

  • Visuals: match the visual to the question. Format, themes, conditional formatting, slicers and filters (visual, page, report level).
  • Storytelling: bookmarks, buttons and the Selection pane, tooltips, drillthrough, sync slicers, navigation and sorting.
  • Usability: mobile layout, accessibility (alt text, tab order, contrast), personalised visuals, export settings, automatic page refresh.
  • Analysis: the Analyze feature, grouping and binning, clustering, forecasting, error bars, anomalies, and AI visuals.
  • Copilot and visual calculations: know what the current outline names and when each is the right tool.
  • Paginated reports: know when a paginated report is the right answer.

Project: a three-page report with an overview, a drillthrough detail page and a custom tooltip, with one bookmark toggle and a mobile layout.

Week 4: manage and secure (15–20%), then review

Goal: publish the report, control who sees what, and keep it refreshed.

  • Workspaces: the four roles (Admin, Member, Contributor, Viewer) and what each can do.
  • Distribution: apps and audiences versus sharing, subscriptions, data alerts and dashboards.
  • Refresh: scheduled refresh, gateways and when one is needed.
  • Governance: endorsement (promote versus certify), sensitivity labels, item-level and semantic model access.
  • Row-level security: static and dynamic roles, USERPRINCIPALNAME, and role membership in the service. Know that workspace members with edit rights bypass RLS.

Project: publish the report, create an RLS role, add yourself to it, test it with View as, and create an app with two audiences.

Review: take the free 20-question practice test mid-week, then repeat the official practice assessment. Spend the remaining days on your lowest domain, using its guide in this section.

If you already build Power BI reports

Compress week 3, because you already design reports. Spend the saved time on what daily use hides: DAX filter context, inactive relationships, calculation groups, privacy levels, reference versus duplicate queries, and the exact permissions of each workspace role.

How to know you are ready

  • You can predict a measure’s result from the model and the filters on a visual before you run it.
  • You can look at a Power Query step list and say what each step does to the row and column count.
  • You can name which workspace role, app setting or RLS configuration meets a stated requirement.
  • You score 80% or more on realistic practice questions twice in a row, on different question sets.

Then book it. See the exam format for the mechanics and the exam day guide for the day itself.