Business Intelligence (With Power BI)

Power BI Course Curriculum Outline

Module 1: Introduction to Power BI

  • Overview of Power BI
    • What is Power BI?
    • Components of Power BI (Power BI Desktop, Power BI Service, Power BI Mobile)
    • Power BI vs other BI tools (Excel, Tableau, etc.)
  • Installing Power BI Desktop
    • Step-by-step installation guide
    • Introduction to Power BI Desktop interface
  • Power BI Ecosystem
    • Understanding Power BI Service
    • Power BI Pro vs. Power BI Premium
    • Data collaboration and sharing options (Workspaces, Apps, and Dashboards)

Module 2: Getting Started with Power BI Desktop

  • Understanding Data Sources
    • Connecting to data (Excel, CSV, SQL, Web, etc.)
    • Basic query transformations with Power Query Editor
  • Loading Data into Power BI
    • Importing data and setting up the Data Model
    • Overview of the Fields pane and Data Model
  • Exploring Power Query Editor
    • Basic data transformations (filtering, sorting, renaming columns, etc.)
    • Merging and appending queries
    • Data cleaning and shaping

Module 3: Visualizing Data in Power BI

  • Creating Basic Visualizations
    • Bar charts, line charts, pie charts, tables
    • Using slicers and filters to interact with reports
  • Advanced Visualizations
    • Treemaps, scatter plots, waterf all charts, etc.
    • Conditional formatting
    • Custom visuals and how to import them
  • Formatting and Customization
    • Visual formatting options (themes, colors, fonts)
    • Tooltips, titles, and axis formatting

Module 4: Data Modeling and Relationships

  • Understanding Data Modeling
    • The importance of data relationships
    • Different types of relationships (one-to-many, many-to-one, etc.)
  • Creating Relationships in Power BI
    • Building and managing relationships between tables
    • Best practices for data model design
  • Introduction to Star Schema and Snowflake Schema
    • Using a Star Schema for efficient data modeling
    • Differences between star schema and snowflake schema

Module 5: Introduction to DAX (Data Analysis Expressions)

  • What is DAX?
    • Introduction to formulas and expressions in Power BI
    • The difference between calculated columns and measures
  • Basic DAX Functions
    • SUM(), AVERAGE(), COUNT(), MIN(), MAX(), etc.
    • Using logical functions (IF(), SWITCH(), etc.)
  • Time Intelligence in DAX
    • Working with dates and time periods (YTD, MTD, QTD)
    • Creating custom time-based measures

Module 6: Advanced DAX and Calculations

  • Advanced DAX Functions
    • CALCULATE(), FILTER(), ALL(), VALUES()
    • Time intelligence functions like SAMEPERIODLASTYEAR(), DATESYTD(), etc.
  • Row-level Security (RLS) in Power BI
    • Understanding RLS concepts
    • Configuring roles and permissions to restrict data access
  • Optimizing DAX for Performance
    • Techniques for improving DAX performance
    • Query plan analysis and best practices

Module 7: Power BI Service: Publishing and Sharing Reports

  • Publishing to Power BI Service
    • How to publish reports and datasets to the Power BI Service
    • Understanding workspaces and apps
  • Sharing and Collaboration
    • Sharing reports and dashboards with colleagues
    • Using Power BI Apps for easier report distribution
  • Power BI Service Features
    • Creating Dashboards
    • Setting up scheduled data refresh
    • Alerts and notifications

Module 8: Power BI for Data Insights and Analysis

  • Creating Interactive Reports
    • Drill-through, drill-down, and other interaction techniques
    • Using slicers for dynamic reporting
  • Analyzing Data Using Power BI
    • Trend analysis, forecasting, and data exploration
    • Using Power BI to make data-driven decisions

Module 9: Power BI Mobile and Advanced Features

  • Using Power BI on Mobile Devices
    • Overview of Power BI Mobile App
    • How to view and interact with reports on mobile devices
  • Advanced Power BI Features
    • Power BI AI capabilities (Quick Insights, Cognitive Services integration)
    • Using Power Automate with Power BI for automating workflows
    • Embedding Power BI in other applications (PowerApps, SharePoint, etc.)

Module 10: Power BI Best Practices and Project

  • Best Practices for Report Design
    • Designing for usability and simplicity
    • Consistency and storytelling with data
  • Real-World Power BI Project
    • End-to-end project that covers data import, transformation, visualization, and sharing
    • Working on a dataset and creating a report/dashboard
    • Presenting findings and key insights

Module 11: Power BI Certification Preparation (Optional)

  • Power BI Certification Overview
    • Preparing for Microsoft Power BI certification exams (DA-100 or PL-300)
    • Tips and strategies for exam preparation
    • Practice questions and review

Additional Course Features:

  • Hands-on Labs & Exercises: Students will work on real-life datasets and build reports from scratch.
  • Quizzes & Assessments: Regular quizzes to reinforce learning.
  • Discussion Forums: A platform for students to ask questions and collaborate.
  • Final Project: A comprehensive project that will allow students to showcase their Power BI skills.

Course Duration & Delivery

  • Duration: Typically 4 to 6 weeks, depending on the pace of learning (3–4 hours per week).
  • Mode of Delivery: Online (self-paced, instructor-led, or blended learning), In-person classroom training.
  • Prerequisites: Basic understanding of data and Excel. No advanced technical knowledge required.

Tools and Software:

Access to Power BI Service for cloud-based activities

Power BI Desktop (Free version)

Power BI Pro (Optional for sharing and collaboration features)