PL-300T00: Microsoft Power BI Data Analyst

Prepare to pass the Power BI Data Analyst Associate Certification Exam in an immersive 3-day course.

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Web 1920 – 86-min

Course Description

This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.

Who Should Attend?

The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises.


About this course

Course Outline

  • Prepare the data (25–30%)

  • Model the data (25–30%)

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

  • Deploy and maintain assets (15–20%)

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 dataset, or create a local dataset

  • 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

  • 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

Deploy and maintain assets (15–20%)

Create and manage workspaces and assets

  • 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

Manage datasets

  • 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.


  • 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.


This will be a virtual event hosted on Microsoft Teams. In the Microsoft Teams platform and sessions, your name, email address, or title may be viewable by other participants. By joining this event, you agree to this experience. 

Need to Train a Team?

 Contact a Cloud Training Specialist to schedule a custom training event for your team!