Master Power BI: Complete Course Outline (Desktop, Cloud, ETL, Analytics)

 

📊 Power BI Course Outline: Desktop, Cloud, ETL, Reporting & Collaboration (Beginner to Advanced 2025)

📌 Introduction

Power BI is a leading business intelligence and data visualization tool that helps organizations turn raw data into insightful reports and dashboards. This course roadmap guides learners through Power BI Desktop, data modeling, ETL processes, cloud deployment, collaboration, and advanced analytics, including the latest 2025 features to create enterprise-grade solutions.

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📘 Detailed Course Outline

Module 1: Introduction to Power BI

• What is Power BI and its ecosystem (Desktop, Service, Mobile)

• Importance of BI and Data Visualization

• Power BI workflow overview: Data → Model → Visualize → Share

• Latest Power BI 2025 features and updates

• Installation and environment setup

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Module 2: Power BI Desktop Basics

• User Interface overview: ribbons, panes, fields, visualizations

• Importing data from multiple sources (Excel, CSV, SQL Server, Oracle, Web, APIs)

• Data connectivity options and connectors

• Data transformation using Power Query Editor

• Creating simple tables, charts, and KPIs

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Module 3: Data Modeling

• Relationships: one-to-one, one-to-many, many-to-many

• Star and snowflake schema

• Creating calculated columns and measures

• DAX basics (SUM, AVERAGE, COUNT, IF, SWITCH)

• Advanced DAX: CALCULATE, FILTER, ALL, RELATED, time intelligence functions

• Role of data modeling in report performance

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Module 4: Report Development & Visualization

• Creating visuals: bar, line, column, pie, scatter, map, table, matrix

• Conditional formatting and custom visuals

• Drill-through, slicers, filters, bookmarks

• Themes, color palettes, and report layouts

• Storytelling with data: dashboards and reports design best practices

• Mobile-friendly report design

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Module 5: Power BI Service (Cloud)

• Power BI workspace overview

• Publishing reports from Desktop to Service

• Dataset and report management

• Scheduled refresh and real-time data updates

• Row-level security (RLS) implementation

• Sharing dashboards and collaboration features

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Module 6: Data Integration & ETL

• Power Query Editor for data cleaning and transformation

• Merge and Append queries

• Handling missing or inconsistent data

• Advanced ETL: pivot/unpivot, split columns, custom columns

• Parameters, functions, and query optimization

• Dataflow creation and reuse in cloud

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Module 7: Advanced Analytics & AI Features

• Quick Insights and AI visuals

• Decomposition trees and key influencers

• Forecasting and trend analysis

• Clustering, grouping, and anomaly detection

• Integration with Python & R scripts for advanced analytics

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Module 8: Collaboration, Governance & Deployment

• Workspaces, apps, and content packs

• Versioning and dataset lineage

• Dataflows vs datasets management

• Sharing reports securely with stakeholders

• Governance, auditing, and monitoring report usage

• Power BI deployment pipelines (Dev → Test → Prod)

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Module 9: Power BI Integration & Automation

• Power BI with Excel, SharePoint, Teams, and Dynamics 365

• Embedding Power BI in applications

• Automating workflows with Power Automate

• Using APIs for programmatic report updates and monitoring

• Integration with SQL, Azure Synapse, and cloud data warehouses

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Module 10: Best Practices & Modern Power BI Features

• Optimizing DAX and data model performance

• Reducing dataset size and improving refresh times

• Designing visually appealing and user-friendly dashboards

• Real-time dashboards and streaming datasets

• Latest 2025 updates: AI integration, Copilot features, enhanced Power Query, and cloud management improvements

• Capstone idea: Combining multiple datasets into a fully interactive enterprise dashboard

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📌 Conclusion

Mastering Power BI equips professionals to turn data into actionable insights, create interactive dashboards, and manage cloud-based BI solutions. This roadmap covers Desktop, ETL, advanced DAX, cloud deployment, collaboration, and modern AI-driven analytics, preparing learners to excel in enterprise data analysis for 2025 and beyond.