Microsoft Power BI Data Analyst (PL-300) - Exams in 2024

About Microsoft Power BI Data Analyst (PL-300) - Exams in 2024

Microsoft Power BI Data Analyst (PL-300)

Microsoft's Power BI system is a suite of software services, applications, and connectors that help businesses transform distinct data sources into cohesive, interactive, and visually engaging insights. An expansive toolkit, Power BI caters to various team roles, including analysts, developers, and sales professionals.

To start working with the Power BI system, the PL-300 exam by Microsoft assesses your proficiency as a data analyst in using Power BI. Passing the exam can arm you with the vital skills needed to create data visualizations, configure data solutions, and support self-service analytics.

PL-300 exam areas of assessment

The PL-300 exam can gauge your proficiency and skills across the following four domain areas:

Prepare the data (25 to 30 percent of the exam). The “prepare the data” section tests your abilities in gathering, cleansing, and restructuring data.

Model the data (25 to 30 percent of the exam). This exam portion evaluates your proficiency in crafting and executing a data model, performing model calculations through data analysis expressions (DAX), and enhancing model performance.

Visualize and analyze the data (25 to 30 percent of the exam). In this segment, your ability to generate reports, improve their usability, and discover patterns and trends within data is tested.

Deploy and maintain items (15 to 20 percent of the exam). The section of the exam focusing on "deploy and maintain items" validates your expertise in setting up and governing workspaces and items and overseeing semantic models.

Prepare the data (25–30%)

Get data from data sources

Identify and connect to a data source

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

Select a shared semantic model, or create a local data model

Choose between DirectQuery, Import, and Dual mode

Change the value in a parameter

Clean the data

Evaluate data, including data statistics and column properties

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

Resolve data import errors

Transform and load the data

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

Model the data (25–30%)

Design and implement a data model

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 model calculations by using DAX

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

Optimize model performance

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

Visualize and analyze the data (25–30%)

Create reports

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

Enhance reports for usability and storytelling

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

Enable personalized visuals in a report

Design and configure Power BI reports for accessibility

Identify patterns and trends

Use the Analyze feature in Power BI

Use grouping, binning, and clustering

Incorporate the Q&A feature in a report

Use AI visuals

Use reference lines, error bars, and forecasting

Detect outliers and anomalies

Create and share scorecards and metrics

Deploy and maintain items (15–20%)

Create and manage workspaces and items

Create and configure a workspace

Assign workspace roles

Configure and update a workspace app

Publish, import, or update items 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

Manage semantic models

Identify when a gateway is required

Configure a semantic model scheduled refresh

Configure row-level security group membership

Provide access to semantic models

Configure automatic page refresh