Design and manage analytics solutions using Power BI (PL-300)

The PL-300: Microsoft Power BI Data Analyst course and exam are designed for individuals aiming to demonstrate their expertise in analyzing data with Power BI. While there are no strict prerequisites mandated by Microsoft, the following foundational skills and knowledge are highly recommended to ensure success:

Prerequisites for the PL-300 Course:

• Basic Data Analysis Knowledge:
• Understanding of data concepts, such as data tables, relationships, and common visualization types.
• Familiarity with basic statistical concepts like averages, sums, and trends.

Proficiency in Microsoft Excel:

• Some experience with Excel functions like pivot tables, charts, and formulas is advantageous.
• Understanding of data sources:
• Basic knowledge of data structures and how to work with different data sources, such as SQL databases, Excel files, or cloud services.

Technical Skills:

• Ability to navigate and use software applications comfortably.
• Familiarity with Power BI Desktop and Power BI Service is beneficial but not mandatory.

General IT Knowledge:

• Awareness of fundamental IT concepts such as file systems, basic networking, and application installation.
• Before starting the PL-300 course or attempting the exam, candidates should spend time familiarizing themselves with Microsoft Power BI through tutorials or hands-on practice. Completing free or introductory Power BI training modules provided by Microsoft Learn can serve as an excellent starting point.
• Please note: If you do not have significant experience with the concepts identified above, we strongly suggest you consider attending either Power BI Desktop for Business Users or Power BI Desktop for Technical Users instead.

Target audience

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

Accessing your courseware and registering attendance with Microsoft

To access your Official Curriculum (MOC) course materials you will need a Microsoft.com/Learn account. In Learn you will also be able to register your completion of the event and receive your achievement badge. You will be issued with a unique code during your event.

By the end of this course, learners will be able to:

• Ingest, cleanse, and transform data
• Model data for performance and scalability
• Design and create reports for data analysis
• Apply and perform advanced report analytics
• Manage and share report assets

Module 1: Get Started with Microsoft Data Analytics

• Roles in data
• Data analysis tasks
• Building blocks of Power BI
• End-to-end analytics with Microsoft Fabric

Module 2: Get data in Power BI

• Identify and connect to a data source
• Select a storage mode
• Data profiling options
• Resolve data import errors

Module 3: Clean, transform, and load data

• Resolve inconsistencies, unexpected or null values, and data quality issues
• Apply data shape transformations to columns and table structures
• Apply user-friendly naming conventions

Module 4: Configure a semantic model

• Set modeling options
• Create and configure relationships
• Configure table and column properties
• Create hierarchies
• Create quick measures
• Create numeric range and field parameters

Module 5: Create DAX calculations in semantic models

• Understand DAX concept and syntax
• Create calculated tables and columns
• Create measures
• Use iterator functions

Module 6: Modify DAX filter context

• Understand filter context
• Use the CALCULATE function to modify filter context
• Use inactive relationships with DAX
• Perform context transition

Module 7: Use DAX time intelligence functions

• Create custom date tables for time intelligence
• Use DAX time intelligence functions

Module 8: Create visual calculations

• Understand visual calculations and how they differ from measures
• Create visual calculations in Power BI Desktop
• Use parameters in visual calculations

Module 9: Design Power BI reports

• Report structure
• Report objects
• Different visualization types
• Filtering techniques

Module 10: Enhance reports for user experience

• Present details and highlight key values
• Build intuitive navigation and app-like experiences
• Enhance user experience using bookmarks, visual headers, and built-in assistance
• Incorporate specialized visuals to meet unique reporting needs

Module 11: Perform analytics in Power BI

• Use the Analyze feature
• Group, bin, and cluster data
• Identify patterns and trends

Module 12: Get started with Copilot in Power BI

• Use Copilot in Power BI during report development
• Prepare semantic models for use with AI
• Interact with data using natural language in Copilot Chat

Module 13: Manage workspaces in Power BI

• Describe the Power BI service and its building blocks
• Create workspaces, assign license modes, and manage access
• Publish reports to the Power BI service

Module 14: Manage semantic models

• Use a Power BI gateway to connect to on-premises data sources
• Configure a scheduled refresh for a semantic model
• Configure incremental refresh settings
• Manage and promote semantic models
• Boost performance with query caching
• Use lineage and impact analysis

Module 15: Choose a content distribution method

• Understand the different content distribution methods available in Power BI
• Create a Power BI app
• Apply data governance principles
• Track a report or dashboard

Module 16: Secure data access in Power BI

• Configure row-level security by using a static method
• Configure row-level security by using a dynamic method

Exams and assessments

There are no formal exams included in this course, but its content is broadly aligned with the Microsoft Certified: Power BI Data Analyst Associate certification. Participants will complete interactive labs and knowledge checks to reinforce learning outcomes.

Hands-on learning

This course includes:

• Hands-on labs to apply key concepts in a real-world environment.