UNF Professional and Lifelong Learning
UNF Professional and Lifelong Learning · Microsoft

Design and Manage Analytics Solutions Using Power BI (PL-300)

LevelIntermediate
Duration3 Days
Experience1 year: Core Data Concepts
Average Salary$82,640
LabsYes

Offered to the Jacksonville and Northeast Florida community through UNF Professional and Lifelong Learning in partnership with Applied Technology Academy — live online or in person, taught by ATA's practitioner instructors.

Course Overview
  • Microsoft course PL-300T00-A. 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. It shows how to access and process data from a range of data sources,
  • including both relational and non-relational sources, and how to manage and deploy reports and
  • dashboards for sharing and content distribution.
  • Three days, intermediate level, aligned to the Data Analyst role and preparing for the
  • Microsoft Certified: Power BI Data Analyst Associate certification.
Course Outline
  • Module 1: Get started with Microsoft data analytics
    • An overview of data analysis, the roles in data and the tasks of a data analyst.
    • The building blocks of Power BI, and a tour of the Power BI service.
  • Module 2: Prepare the data (exam weighting 25-30%)
    • Get or connect to data - identify and connect to data sources or a shared semantic model;
    • change data source settings including credentials and privacy levels; choose between
    • DirectLake, DirectQuery and Import; create and modify parameters.
    • Profile and clean the data - evaluate data using data statistics and column properties;
    • resolve inconsistencies, unexpected or null values and data quality issues; resolve import errors.
    • Transform and load the data - select column data types; create and transform columns; group and
    • aggregate rows; pivot, unpivot and transpose; convert semi-structured data to a table; create
    • fact and dimension tables; reference versus duplicate queries; merge and append queries;
    • create keys for relationships; configure data loading for queries.
  • Module 3: Model the data (exam weighting 25-30%)
    • Design and implement a data model - configure table and column properties; implement
    • role-playing dimensions; define cardinality and cross-filter direction; create a common date
    • table; identify use cases for calculated columns and calculated tables.
    • Create model calculations by using DAX - single aggregation measures; the CALCULATE function;
    • time intelligence measures; basic statistical functions; semi-additive measures; quick
    • measures; calculated tables and columns; calculation groups.
    • Optimize model performance - remove unnecessary rows and columns; identify poorly performing
    • measures, relationships and visuals using Performance Analyzer and the DAX query view;
    • improve performance by reducing granularity.
  • Module 4: Visualize and analyze the data (exam weighting 25-30%)
    • Create reports - select, format and configure visuals; create a narrative visual with Copilot;
    • apply and customize a theme; apply conditional formatting, slicing and filtering; use Copilot to create a report page and suggest its content; configure the report page; choose when to use
    • a paginated report; create visual calculations by using DAX.
    • Enhance reports for usability and storytelling - bookmarks, custom tooltips, interactions
    • between visuals, report navigation, sorting, sync slicers, grouping and layering with the
    • Selection pane, drillthrough navigation, export settings, mobile layouts, personalization,
    • accessibility and automatic page refresh.
    • Identify patterns and trends - the Analyze feature; grouping, binning and clustering; AI
    • visuals; reference lines, error bars and forecasting; outlier and anomaly detection; using
    • Copilot to summarize the underlying semantic model.
  • Module 5: Manage and secure Power BI (exam weighting 15-20%)
    • Create and manage workspaces and assets - create and configure a workspace; configure and
    • update an app; publish, import or update items; create dashboards; choose a distribution
    • method; configure subscriptions and data alerts; promote or certify content; identify when a
    • gateway is required; configure a semantic model scheduled refresh.
    • Secure and govern Power BI items - assign workspace roles; configure item-level access and
    • access to semantic models; implement row-level security roles and group membership; apply
    • sensitivity labels.
    • Exam weightings above follow Microsoft's skills-measured list for PL-300 as of April 20, 2026.
Intended Audience
  • Data professionals and business intelligence professionals who want to learn how to accurately
  • perform data analysis using Power BI.
  • Individuals who develop reports that visualize data from data platform technologies that exist
  • both in the cloud and on-premises.
  • Analysts who work with business stakeholders to identify requirements, and alongside analytics
  • engineers and data engineers to acquire data.
Prerequisites
  • 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
  • DP-900 Microsoft Azure Data Fundamentals is recommended
  • Proficiency with Power Query and Data Analysis Expressions (DAX)