We provide course about PL-300: Design and Manage Analytics Solutions Using Power BI. The Design and manage analytics solutions using Power BI course is designed to build expertise in data analysis, modeling, and visualization using Power BI’s full capabilities.
Course description:
Participants will learn to connect to and transform data, build semantic models, and create effective reports and calculations using enhanced DAX functions and updated filter context labs. The PL-300 course also introduces Microsoft Fabric for integrated analytics workflows, alongside refreshed modules on content distribution, workspace management, and secure data access. With the removal of classic dashboards and a new emphasis on collaboration and scalability, this course prepares learners for both the PL-300 exam and real-world data challenges in enterprise and self-service BI environments.
Course outline:
Module 1 - Get started with Microsoft data analytics:
Discover data analysis:
• Learn about the roles in data
• Learn about the tasks of a data analyst
Get started building with Power BI:
• How Power BI services and applications work together
• Explore how Power BI can make your business more efficient
• How to create compelling visuals and reports
Create interactive reports using Copilot for Power BI:
• Design semantic model
• Create visuals and reports
• Create summaries
Module 2 - Prepare data for analysis with Power BI:
Get data in Power BI:
• Identify and connect to a data source
• Get data from a relational database, like Microsoft SQL Server
• Get data from a file, like Microsoft Excel
• Get data from applications
• Get data from Azure Analysis Services
• Select a storage mode
• Fix performance issues
• Resolve data import errors
Clean, transform, and load data in Power BI:
• Resolve inconsistencies, unexpected or null values, and data quality issues
• Apply user-friendly value replacements
• Profile data so you can learn more about a specific column before using it
• Evaluate and transform column data types
• Apply data shape transformations to table structures
• Combine queries
• Apply user-friendly naming conventions to columns and queries
• Edit M code in the Advanced Editor
Module 3 - Model data with Power BI:
Describe Power BI Desktop models:
• Describe the structure of a Power BI Desktop model.
• Explain star schema design basics.
• Define the term analytic query and its phases.
• Describe how fields can be used to configure a report visual, which then generates an analytic query
Choose a Power BI model framework:
• Describe Power BI model fundamentals
• Determine when to develop an import model
• Determine when to develop a DirectQuery model
• Determine when to develop a composite model
• Choose an appropriate Power BI model framework
Design a semantic model in Power BI:
• Create common date tables
• Configure many-to-many relationships
• Resolve circular relationships
• Design star schemas
Write DAX formulas for Power BI Desktop models:
• Describe the different DAX calculation types
• Write DAX formulas
• Describe DAX data types
• Work with DAX functions
• Use DAX operators
• Use DAX variables
Add measures to Power BI Desktop models:
• Determine when to use implicit and explicit measures
• Create simple measures
• Create compound measures
• Create quick measures
• Describe similarities of, and differences between, a calculated column and a measure
Add calculated tables and columns to Power BI Desktop models
• Create calculated tables
• Create calculated columns
• Identify row context
• Determine when to use a calculated column in place of a Power Query custom column
• Add a date table to your model by using DAX calculations
Use DAX time intelligence functions in Power BI Desktop models:
• Define time intelligence
• Use common DAX time intelligence functions
• Create useful intelligence calculations
Optimize a model for performance in Power BI:
• Review the performance of measures, relationships, and visuals
• Use variables to improve performance and troubleshooting
• Improve performance by reducing cardinality levels
• Optimize DirectQuery models with table level storage
• Create and manage aggregations
Enforce Power BI model security:
• Restrict access to Power BI model data with RLS
• Restrict access to Power BI model objects with OLS
• Apply good development practices to enforce Power BI model security
Module 4 - Build Power BI visuals and reports:
• Scope report design requirements:
• Determine business goals
• Identify your audience
• Determine report types
• Define user interface requirements
• Define user experience requirements
Design Power BI reports:
• Learn about the structure of a Power BI report
• Learn about report objects
• Select the appropriate visual type to use
Create visual calculations in Power BI Desktop:
• Understand visual calculations and how they differ from measures
• Create visual calculations in Power BI Desktop
• Use parameters in visual calculations
Configure Power BI report filters:
• Design reports for filtering
• Design reports with slicers
• Design reports by using advanced filtering techniques
• Apply consumption-time filtering
• Select appropriate report filtering techniques
Enhance Power BI report designs for the user experience:
• Design reports to show details
• Design reports to highlight values
• Design reports that behave like apps
• Work with bookmarks
• Design reports for navigation
• Work with visual headers
• Design reports with built-in assistance
• Use specialized visuals
Perform analytics in Power BI:
• Explore statistical summary
• Identify outliers with Power BI visuals
• Group and bin data for analysis
• Apply clustering techniques
• Conduct time series analysis
• Use the Analyze feature
• Use advanced analytics custom visuals
• Review Quick insights
• Apply AI Insights
Create paginated reports:
• Get data
• Create a paginated report
• Work with charts and tables on the report
• Publish the report
Module 5 - Manage workspaces and datasets in Power BI:
Create and manage workspaces in Power BI:
• Create and manage Power BI workspaces and items
• Distribute a report or dashboard
• Monitor usage and performance
• Recommend a development lifecycle strategy
• Troubleshoot data by viewing its lineage
• Configure data protection
Manage semantic models in Power BI:
• Use a Power BI gateway to connect to on-premises data sources
• Configure a scheduled refresh for a semantic modes
• Configure incremental refresh settings
• Manage and promote semantic models
• Troubleshoot service connectivity
• Boost performance with query caching (Premium)
Create dashboards in Power BI:
• Set a mobile view
• Add a theme to the visuals in your dashboard
• Add real-time semantic model visuals to your dashboards
• Pin a live report page to a dashboard
Implement row-level security:
• Configure row-level security by using a static method
• Configure row-level security by using a dynamic method
• Improve report performance
Target audience:
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. Job role: Data Analyst.
Prerequisites:
• Understanding of core data concepts
• Knowledge of working with relational and non-relational data
• Knowledge of data analysis and visualization concepts
Language:
• English course material
• Norwegian or english speaking instructor
Course material:
The course fee includes digital course documentation and hands-on labs, lunch and refreshments for in class events only.
Certification:
This course will help you prepare for the exam Microsoft Certified: Power BI Data Analyst Associate. The certification focuses on demonstrating methods and best practices for modeling, visualizing, and analyzing data using Microsoft Power BI.
Assessed on this exam:
• Prepare the data
• Model the data
• Visualize and analyze the data
• Manage and secure Power BI