PL-300 study plan

Connect Power BI Desktop to at least four source types (Excel/CSV, a relational database, a web source, and a folder) and set the correct storage mode for each

Profile every imported table with Column quality, Column distribution, and Column profile to identify nulls, distinct values, and outliers

Document the grain of each source table and flag duplicate keys before any transformation

Apply a naming convention to queries and columns and remove unused columns to reduce model size

Clean and shape data with Power Query: change types, split and merge columns, unpivot a wide table into a tall fact-style table, and remove errors

Combine queries (append and merge) into a consolidated fact table and build conformed dimension tables

Design a star schema by identifying fact vs. dimension tables and marking the date table as a Date table

Create a basic measure and a calculated column and explain when to use each

Replace hard-coded values with parameters to make the query reusable

Build one-to-many relationships between the fact and each dimension and verify filter direction and cardinality

Write DAX measures using CALCULATE, FILTER, DIVIDE, and SUMX instead of implicit measures

Implement time intelligence measures (YTD, prior-year comparison, rolling average) against the marked date table

Create at least one hierarchy and validate cross-filter behavior in a matrix visual

Reduce model size by hiding technical columns and removing unused columns

Choose appropriate visuals (card, bar, line, matrix, scatter) for each analytical question and justify the choice

Apply slicers, filters, drill-through, and cross-filtering to a two-page report

Format visuals for accessibility: alt text, tab order, readable contrast, and clear titles

Optimize a slow visual by reviewing the model relationships and DAX rather than guessing

Add analytics features to visuals: reference lines, trend lines, forecasting, and anomaly detection

Build a what-if parameter and show its effect on a measure in a visual

Create groups and bins and use them in a visual

Configure a custom tooltip page and a bookmarks-based navigation

Configure row limits and aggregations to keep a large-visual report responsive

Publish the report to a workspace and pin visuals to a dashboard

Configure a scheduled refresh for the dataset and confirm credentials are stored correctly

Create a Power BI app from the workspace and control its audience and content

Set up a data alert and a subscription on a dashboard tile

Identify when to use a shared dataset versus a duplicate report

Implement static and dynamic row-level security roles and test each with the 'View as role' feature

Apply sensitivity labels and configure export and download restrictions for a dataset

Configure a deployment pipeline across Development, Test, and Production and promote content once

Manage workspace roles (Admin, Member, Contributor, Viewer) and assign the minimum necessary permission

Review usage metrics and the lineage view to trace report-to-source dependencies

Retake a timed 60-question practice set and log the domain of every missed question

Re-do every missed objective as a hands-on task in Power BI Desktop rather than re-reading notes

Rebuild one end-to-end mini-project from raw data to published secured report in under 90 minutes

Review the Power Query, DAX, and security cheat sheets you wrote in weeks 2, 3, and 7