Introduction

This course will provide you the knowledge to understand and implement the key principles about the aspects of Data analysis and modeling in Power BI using tools such as Power BI Desktop and accompanying the cloud service for publishing and consumption of BI Assets. This course would then cover the basics of report development embedded analytics in Power BI to embed the content into custom applications, Real time dashboarding and advanced analytics involving data science and development in Power BI.

Training objectives

• Learn how to ingest, clean, transform, and model data

• Model data for performance and scalability

• Design and create paginated reports to analyze data with Power BI

• Apply and perform advanced report analytics

• Manage and share report assets

• Create paginated reports in Power BI

Target Audience

The audience for this course is:

• Data professionals

• Business intelligence professionals

• This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist both in the cloud and on-premises.

Training outlines

Day 1: Introduction to Data Analytics & Power BI

• Data analytics fundamentals and Microsoft ecosystem overview
• Roles and responsibilities of a data analyst
• Overview of Power BI products and services
• Getting started with Power BI Service

Day 2: Data Preparation & Transformation

• Connecting to multiple data sources (Dataverse, data flows, etc.)
• Understanding connection methods and performance implications
• Data cleaning, profiling, and transformation techniques
• Handling data errors and optimizing performance
• Lab: Preparing and transforming data in Power BI Desktop

Day 3: Data Modeling & DAX Fundamentals

• Introduction to data modeling concepts
• Working with tables, relationships, dimensions, and hierarchies
• Creating and managing relationships and cardinality
• Introduction to DAX and filter context
• Creating measures, calculated columns, and calculated tables
• Basic KPIs, rankings, and time intelligence

Day 4: Reporting, Visualization & Dashboards

• Designing effective and interactive report layouts
• Building visualizations and enhancing user experience
• Drillthrough, slicers, bookmarks, and conditional formatting
• Creating dashboards and real-time monitoring
• Sharing, publishing, and managing Power BI content
• Lab: Designing and enhancing Power BI reports and dashboards

Day 5: Advanced Analytics, Security & Optimization

• Advanced analytics: forecasting, outliers, and AI visuals
• Decomposition Tree and Key Influencers analysis
• Model optimization and performance tuning
• Dataset management and refresh processes
• Power BI security and Row-Level Security (RLS)
• Workspace management, collaboration, and app publishing