Power BI Data Analysis and AI Dashboard Course

Overview

Power BI Data Analysis and AI Dashboard Course is a five-day intermediate course for business analysts, reporting professionals, data teams, performance managers, and decision-support professionals, who leave with a Power BI AI Dashboard Review Pack. Participants connect prepared data to semantic models, DAX measures, visual analysis, AI-assisted exploration, forecasting, anomaly review, dashboard governance, and controlled publication. Agile Leaders Training Center provides training in Power BI data analysis and AI dashboards.

Who Should Attend

• Teams responsible for management reporting and performance analysis
• Teams responsible for data preparation, semantic models, and measures
• Teams responsible for interactive reports and executive dashboards
• Teams responsible for forecasting, anomaly review, and decision support
• Teams responsible for analytics governance, access, refresh, and publication

The course assumes participants use Power BI Desktop or consume Power BI reports and leaves out data engineering, advanced DAX optimization, Fabric administration, custom visual development, and machine-learning model training.

Departments and Industries

The course supports Power BI analysis across finance, operations, sales, public services, healthcare, education, and industrial organizations.

• Finance, budgeting, and performance management
• Operations, supply chain, and quality teams
• Sales, marketing, and customer analysis
• Public service and administrative reporting
• Healthcare and education analytics
• Industrial and asset performance reporting

Learning Objectives

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

• Apply Power Query preparation and data-quality checks
• Build semantic models, relationships, and DAX measures
• Analyze visual design, filters, interactions, and accessibility
• Use AI-assisted exploration, forecasting, and anomaly review
• Evaluate security, refresh, publication, and governance controls
• Build a Power BI AI Dashboard Review Pack

Course Agenda

Day 1: Data Preparation and Analysis Context

• Power BI Analysis Use Case Canvas
• Power Query Data Preparation Workflow
• Column Quality, Distribution, and Profile Review
• Data Type, Missing Value, and Error Checklist
• Source-to-Report Lineage Map

Day 2: Semantic Models and DAX

• Star Schema Fact and Dimension Design
• Relationship Cardinality and Filter Direction Check
• Date Table and Time Analysis Pattern
• DAX Measure and Filter Context Method
• Semantic Model Quality Review Sheet

Day 3: Reports and Dashboard Design

• Visual Selection and Analytical Question Matrix
• Report Page Layout and Information Hierarchy
• Filter, Slicer, Drillthrough, and Interaction Plan
• Dashboard Tile and Key Indicator Composition
• Accessibility and Mobile View Checklist

Day 4: AI Insights and Governance

• Copilot for Power BI Exploration Prompt Guide
• Quick Insights and Generated Finding Review
• Forecast and Anomaly Evidence Assessment
• Row-Level Security Concept and Access Matrix
• Refresh, Publication, Sharing, and Governance Plan

Day 5: Power BI Dashboard Practice

• Suggested Exercise: Prepare and Profile a Dataset
• Suggested Exercise: Build Measures and Validate Results
• Suggested Exercise: Design and Challenge a Dashboard
• Suggested Exercise: Review AI-Assisted Findings and Controls
• Capstone Exercise: Power BI AI Dashboard Review Pack

Practical Exercises

The course uses suggested activities to connect Power BI analysis choices with reviewable business evidence.

• Suggested activity: prepare a finance or operations dataset and document types, errors, gaps, transformations, and lineage
• Suggested activity: build relationships and measures, then test totals, filters, time context, and edge cases
• Suggested activity: design a dashboard for sales or service performance and review hierarchy, interactions, accessibility, and mobile use
• Suggested activity: assemble a review pack covering AI findings, forecasts, anomalies, security, refresh, publication, and ownership

FAQs

Who suits Power BI data analysis and AI dashboard training, and what does it assume?

The course suits analysts and reporting teams who prepare, model, visualize, review, or publish business data. It assumes basic Power BI familiarity and data-analysis concepts but not advanced DAX, data engineering, or administration.

How does Power BI AI dashboard training differ from a general business intelligence course?

Power BI AI dashboard training applies analysis, modeling, measures, visuals, AI-assisted findings, governance, and publication inside one platform. General business intelligence courses often compare wider architectures, platforms, data warehouses, and operating models.

How does a semantic model improve Power BI analysis?

A semantic model organizes tables, relationships, hierarchies, properties, and measures so reports calculate and filter consistently. Participants review its structure before trusting dashboard results or AI-assisted findings.

How should AI-assisted Power BI insights be reviewed?

AI-assisted insights should be checked against the semantic model, filters, measure definitions, source quality, time context, business meaning, and supporting visuals. The course treats generated findings as evidence to validate rather than conclusions to accept automatically.

What controls support reliable Power BI dashboard publication?

Reliable publication requires defined owners, access rules, refresh checks, approved sources, measure definitions, quality review, sharing choices, and a process for correcting or retiring content.

Conclusion

Participants take back a Power BI AI Dashboard Review Pack linking prepared data, semantic models, DAX, visual design, AI-assisted exploration, forecasting, anomalies, security, refresh, and publication. It gives teams a repeatable way to review dashboard evidence. It keeps analytical decisions traceable to sources, calculations, and accountable owners.