PL-300T00: Microsoft Power BI Data Analyst

• Prepare the data (25–30%)

• Model the data (25–30%)

• Visualize and analyze the data (25–30%)

• Deploy and maintain assets (15–20%)

• Identify and connect to a data source

• Change data source settings, including credentials, privacy levels, and data source locations

• Select a shared dataset, or create a local dataset

• Choose between DirectQuery, Import, and Dual mode

• Change the value in a parameter

• Evaluate data, including data statistics and column properties

• Resolve inconsistencies, unexpected or null values, and data quality issues

• Resolve data import errors

• Select appropriate column data types

• Create and transform columns

• Transform a query

• Design a star schema that contains facts and dimensions

• Identify when to use reference or duplicate queries and the resulting impact

• Merge and append queries

• Identify and create appropriate keys for relationships

• Configure data loading for queries

• Configure table and column properties

• Implement role-playing dimensions

• Define a relationship's cardinality and cross-filter direction

• Create a common date table

• Implement row-level security roles

• Create single aggregation measures

• Use CALCULATE to manipulate filters

• Implement time intelligence measures

• Identify implicit measures and replace with explicit measures

• Use basic statistical functions

• Create semi-additive measures

• Create a measure by using quick measures

• Create calculated tables

• Improve performance by identifying and removing unnecessary rows and columns

• Identify poorly performing measures, relationships, and visuals by using Performance Analyzer

• Improve performance by choosing optimal data types

• Improve performance by summarizing data

• Identify and implement appropriate visualizations

• Format and configure visualizations

• Use a custom visual

• Apply and customize a theme

• Configure conditional formatting

• Apply slicing and filtering

• Configure the report page

• Use the Analyze in Excel feature

• Choose when to use a paginated report

• Configure bookmarks

• Create custom tooltips

• Edit and configure interactions between visuals

• Configure navigation for a report

• Apply sorting

• Configure sync slicers

• Group and layer visuals by using the Selection pane

• Drill down into data using interactive visuals

• Configure export of report content, and perform an export

• Design reports for mobile devices

• Incorporate the Q&A feature in a report

• Use the Analyze feature in Power BI

• Use grouping, binning, and clustering

• Use AI visuals

• Use reference lines, error bars, and forecasting

• Detect outliers and anomalies

• Create and share scorecards and metrics

• Create and configure a workspace

• Assign workspace roles

• Configure and update a workspace app

• Publish, import, or update assets in a workspace

• Create dashboards

• Choose a distribution method

• Apply sensitivity labels to workspace content

• Configure subscriptions and data alerts

• Promote or certify Power BI content

• Manage global options for files

• Identify when a gateway is required

• Configure a dataset scheduled refresh

• Configure row-level security group membership

• Provide access to datasets

Successful Data Analysts start this role with experience of working with data in the cloud.

Specifically:

• Understanding core data concepts.

• Knowledge of working with relational data in the cloud.

• Knowledge of working with non-relational data in the cloud.

• Knowledge of data analysis and visualization concepts.