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  • Microsoft Power BI Business Intelligence Syllabus tailored for computer students at your coaching institute. This syllabus is structured module-wise, covering foundational to advanced topics to equip students with the skills needed to create, analyze, and share insightful business intelligence reports and dashboards using Microsoft Power BI.
  • Microsoft Power BI Business Intelligence Syllabus
  • Course Overview
  • This course provides an in-depth exploration of Microsoft Power BI, a leading business intelligence tool used for data visualization, transformation, and analysis. Students will learn to connect to various data sources, create interactive reports and dashboards, perform advanced data modeling, and share insights across organizations. The course combines theoretical knowledge with hands-on projects to ensure practical proficiency in Power BI.
  • Learning Outcomes
  • By the end of this course, students will be able to:
  • Understand Power BI Components: Navigate and utilize Power BI Desktop, Power BI Service, and Power BI Mobile.
  • Connect to Data Sources: Import and transform data from various sources using Power Query.
  • Data Modeling: Create relationships, calculated columns, and measures using DAX (Data Analysis Expressions).
  • Create Visualizations: Design and customize interactive reports and dashboards.
  • Advanced Analytics: Implement advanced data analysis techniques and visual storytelling.
  • Share and Collaborate: Publish reports, create dashboards, and collaborate using Power BI Service.
  • Implement Security: Manage data security and access within Power BI.
  • Automate Tasks: Utilize Power BI’s automation features and integrate with other Microsoft tools.
  • Module 1: Introduction to Microsoft Power BI
  • Objective: To provide an overview of Power BI, its components, and its role in business intelligence.
  • 1.1 What is Power BI?
  • Overview:
    • Introduction to Business Intelligence (BI) and its importance.
    • Overview of Power BI and its place within the Microsoft Power Platform.
  • Key Components:
    • Power BI Desktop
    • Power BI Service
    • Power BI Mobile
    • Power BI Gateway
    • Power BI Report Server
  • 1.2 Power BI Desktop Interface and Navigation
  • Navigating Power BI Desktop:
    • Ribbon and its tabs (Home, Insert, Modeling, etc.).
    • Report View, Data View, and Model View.
    • Fields pane, Visualizations pane, and Filters pane.
  • Creating a New Power BI Project:
    • Starting a new project and saving files.
    • Understanding the workspace and layout.
  • 1.3 Getting Started with Power BI Service
  • Introduction to Power BI Service:
    • Overview of the cloud-based Power BI platform.
    • Key features: dashboards, reports, datasets, workspaces.
  • Power BI Mobile:
    • Accessing reports and dashboards on mobile devices.
    • Key functionalities and navigation.
  • 1.4 Practical Exercise:
  • Install Power BI Desktop.
  • Navigate through the Power BI Desktop interface.
  • Create and save a simple Power BI project.
  • Module 2: Connecting to Data Sources
  • Objective: To teach students how to connect Power BI to various data sources and perform initial data transformations.
  • 2.1 Importing Data from Excel and CSV Files
  • Connecting to Excel:
    • Importing data from Excel workbooks.
    • Selecting specific sheets and ranges.
  • Importing CSV Files:
    • Connecting to and importing CSV data.
    • Handling delimiters and data types.
  • 2.2 Connecting to Databases
  • SQL Server:
    • Connecting to SQL Server databases.
    • Importing data using SQL queries.
  • Other Databases:
    • Overview of connecting to Oracle, MySQL, PostgreSQL, etc.
    • Importing and managing data connections.
  • 2.3 Using Power Query for Data Transformation
  • Introduction to Power Query:
    • Overview of the Power Query Editor.
    • Basic transformations: filtering rows, removing columns, renaming fields.
  • Advanced Data Transformation:
    • Merging and appending queries.
    • Pivoting and unpivoting data.
    • Handling missing or duplicate data.
  • 2.4 Connecting to Online Services and APIs
  • Web Data:
    • Importing data from web pages.
    • Connecting to REST APIs.
  • Cloud Services:
    • Connecting to Azure, SharePoint, Google Analytics, etc.
    • Importing and refreshing cloud data.
  • 2.5 Practical Exercise:
  • Connect to an Excel and a SQL Server data source.
  • Perform basic and advanced data transformations using Power Query.
  • Import data from an online service or API.
  • Module 3: Data Modeling
  • Objective: To enable students to create robust data models by establishing relationships and utilizing DAX for advanced calculations.
  • 3.1 Creating Relationships Between Tables
  • Understanding Data Relationships:
    • One-to-One, One-to-Many, and Many-to-Many relationships.
  • Establishing Relationships:
    • Using the Model View to create and manage relationships.
    • Enforcing referential integrity.
  • 3.2 Calculated Columns and Measures
  • Calculated Columns:
    • Creating new columns using DAX formulas.
    • Examples and use cases.
  • Measures:
    • Creating measures for dynamic calculations.
    • Difference between calculated columns and measures.
  • 3.3 Introduction to DAX (Data Analysis Expressions)
  • Basic DAX Syntax:
    • Understanding the structure of DAX formulas.
    • Common functions: SUM, AVERAGE, COUNT, etc.
  • Advanced DAX Functions:
    • Time intelligence functions.
    • Logical functions (IF, AND, OR).
    • Lookup functions (RELATED, LOOKUPVALUE).
  • 3.4 Hierarchies and Calculated Tables
  • Creating Hierarchies:
    • Building hierarchical structures for drill-down capabilities.
  • Calculated Tables:
    • Creating tables using DAX for specific analysis needs.
  • 3.5 Practical Exercise:
  • Create relationships between multiple tables.
  • Develop calculated columns and measures using DAX.
  • Implement hierarchies for enhanced data navigation.
  • Module 4: Creating Visualizations
  • Objective: To teach students how to create and customize a variety of visualizations to represent data effectively.
  • 4.1 Overview of Visualization Types
  • Standard Visuals:
    • Bar and column charts, line charts, pie charts, etc.
  • Advanced Visuals:
    • Waterfall charts, funnel charts, maps, and gauges.
  • Custom Visuals:
    • Importing and using custom visuals from the Power BI marketplace.
  • 4.2 Designing Interactive Reports
  • Report Layout and Formatting:
    • Arranging visuals for optimal readability.
    • Using themes and formatting options.
  • Interactivity Features:
    • Slicers, filters, and drill-throughs.
    • Cross-filtering and highlighting between visuals.
  • 4.3 Using Maps and Geospatial Data
  • Map Visualizations:
    • Creating basic and filled maps.
    • Using ArcGIS maps for advanced geospatial analysis.
  • Customizing Map Visuals:
    • Adding layers, data points, and custom regions.
  • 4.4 Incorporating Multimedia and Images
  • Adding Images and Icons:
    • Embedding images within reports for better context.
  • Using Media Elements:
    • Adding videos and interactive media to reports.
  • 4.5 Practical Exercise:
  • Create various standard and advanced visualizations.
  • Design an interactive report using slicers and cross-filtering.
  • Incorporate maps and multimedia elements into a Power BI report.
  • Module 5: Advanced Data Analysis
  • Objective: To equip students with advanced data analysis techniques to derive deeper insights from their data.
  • 5.1 Time Intelligence and Forecasting
  • Time-Based Analysis:
    • Using DAX for year-over-year and month-over-month comparisons.
  • Forecasting:
    • Implementing forecasting models within Power BI.
    • Analyzing trends and predicting future values.
  • 5.2 What-If Parameters
  • Creating What-If Scenarios:
    • Setting up parameter tables and slicers.
    • Analyzing different business scenarios dynamically.
  • 5.3 Advanced DAX Calculations
  • Complex Measures:
    • Implementing nested DAX functions.
    • Utilizing CALCULATE for context transition.
  • Context in DAX:
    • Understanding row context vs. filter context.
    • Applying context transition in calculations.
  • 5.4 Statistical Analysis and R Integration
  • Basic Statistical Functions:
    • Using Power BI’s statistical capabilities for data analysis.
  • R and Python Integration:
    • Incorporating R scripts and Python scripts for advanced analytics.
    • Creating custom visuals using R and Python.
  • 5.5 Practical Exercise:
  • Implement time intelligence functions and forecasting models.
  • Create and use What-If parameters for scenario analysis.
  • Develop advanced DAX measures and integrate R scripts for statistical analysis.
  • Module 6: Dashboards and Storytelling
  • Objective: To enable students to design compelling dashboards and utilize storytelling techniques for effective data presentation.
  • 6.1 Designing Dashboards
  • Dashboard Principles:
    • Best practices for dashboard design.
    • Balancing aesthetics and functionality.
  • Combining Multiple Reports:
    • Pinning visuals from different reports into a single dashboard.
  • Using Tiles and Widgets:
    • Customizing tiles with KPIs, images, and text boxes.
  • 6.2 Storytelling with Data
  • Narrative Techniques:
    • Structuring reports to tell a compelling story.
    • Highlighting key insights and trends.
  • Annotations and Callouts:
    • Adding annotations to emphasize important data points.
    • Using callouts for additional context.
  • 6.3 Mobile-Optimized Dashboards
  • Designing for Mobile:
    • Creating responsive dashboards for mobile devices.
    • Using the Power BI Mobile app for accessing dashboards on the go.
  • Interactivity on Mobile:
    • Ensuring touch-friendly interactions and navigation.
  • 6.4 Practical Exercise:
  • Design a comprehensive dashboard incorporating multiple visualizations and tiles.
  • Apply storytelling techniques to present data insights effectively.
  • Create a mobile-optimized version of the dashboard and test it on a mobile device.
  • Module 7: Sharing and Collaboration
  • Objective: To teach students how to share their Power BI reports and collaborate effectively within an organization.
  • 7.1 Publishing Reports to Power BI Service
  • Publishing Process:
    • Steps to publish Power BI Desktop reports to Power BI Service.
  • Managing Workspaces:
    • Creating and organizing workspaces for different teams or projects.
  • Setting Up Data Refresh:
    • Configuring scheduled data refresh to keep reports up-to-date.
  • 7.2 Sharing Dashboards and Reports
  • Sharing Options:
    • Sharing dashboards and reports with specific users or groups.
    • Understanding permissions and access levels.
  • Embedding Reports:
    • Embedding Power BI reports into websites, SharePoint, or other applications.
  • Power BI Apps:
    • Creating and distributing Power BI apps for broader access within the organization.
  • 7.3 Collaborating with Teams
  • Power BI Collaboration Features:
    • Using comments and annotations within reports.
    • Collaborating on dashboards in real-time.
  • Integration with Microsoft Teams:
    • Embedding Power BI dashboards in Teams channels.
    • Leveraging Teams for report sharing and collaboration.
  • 7.4 Practical Exercise:
  • Publish a Power BI report to the Power BI Service.
  • Share the report with peers and set appropriate permissions.
  • Embed a report into a SharePoint site or Microsoft Teams channel.
  • Configure scheduled data refresh for a published report.
  • Module 8: Power BI Administration and Security
  • Objective: To provide students with knowledge on administering Power BI environments and implementing security best practices.
  • 8.1 Power BI Administration Basics
  • Admin Roles:
    • Understanding Power BI admin roles and responsibilities.
  • Managing Users and Licenses:
    • Assigning and managing Power BI licenses.
    • Adding and removing users within the Power BI Service.
  • 8.2 Data Security and Governance
  • Row-Level Security (RLS):
    • Implementing RLS to restrict data access based on user roles.
  • Data Classification and Sensitivity Labels:
    • Applying sensitivity labels to classify and protect data.
  • Audit Logs and Monitoring:
    • Using audit logs to track user activities and report access.
    • Monitoring usage and performance metrics.
  • 8.3 Compliance and Data Privacy
  • Compliance Standards:
    • Understanding GDPR, HIPAA, and other compliance requirements.
  • Data Privacy Practices:
    • Ensuring data privacy through secure data handling and storage practices.
  • 8.4 Practical Exercise:
  • Implement Row-Level Security in a Power BI report.
  • Assign and manage user roles and permissions within Power BI Service.
  • Apply sensitivity labels to datasets and monitor audit logs for compliance.
  • Module 9: Power BI Integration and Extensibility
  • Objective: To explore how Power BI integrates with other Microsoft and third-party applications, enhancing its functionality and reach.
  • 9.1 Integrating Power BI with Other Microsoft Tools
  • Excel Integration:
    • Importing and exporting data between Excel and Power BI.
    • Using Analyze in Excel feature for in-depth analysis.
  • SharePoint Integration:
    • Embedding Power BI reports in SharePoint Online.
    • Utilizing Power BI web parts for seamless data access.
  • Microsoft Flow (Power Automate) Integration:
    • Automating workflows with Power BI and Power Automate.
    • Triggering actions based on data events in Power BI.
  • 9.2 Using Power BI APIs and SDKs
  • Power BI REST API:
    • Automating tasks and integrating Power BI with custom applications.
  • Power BI Embedded:
    • Embedding Power BI reports and dashboards into web applications.
  • Custom Visual Development:
    • Creating custom visuals using Power BI Developer Tools.
  • 9.3 Integration with Third-Party Services
  • Connecting to External Data Sources:
    • Integrating with Salesforce, Google Analytics, and other third-party services.
  • Enhancing Functionality with Add-Ons:
    • Utilizing Power BI Marketplace for additional functionalities and visuals.
  • 9.4 Practical Exercise:
  • Embed a Power BI report into a SharePoint Online page.
  • Use Power Automate to create a workflow that triggers based on Power BI data events.
  • Develop and import a custom visual from Power BI Marketplace.
  • Module 10: Final Project and Course Review
  • Objective: To apply all learned concepts in a comprehensive project, demonstrating proficiency in Power BI.
  • 10.1 Final Project: Business Intelligence Solution
  • Project Requirements:
    • Design and implement a complete business intelligence solution for a real-life scenario (e.g., sales analysis, financial reporting, customer insights).
  • Project Components:
    • Data connection and transformation.
    • Data modeling with relationships and DAX measures.
    • Creating interactive reports and dashboards.
    • Implementing advanced analytics and visual storytelling.
    • Publishing and sharing the solution via Power BI Service.
  • Project Execution:
    • Planning the BI solution based on scenario requirements.
    • Building the Power BI solution step-by-step with guidance.
    • Testing and refining the solution for accuracy and usability.
  • 10.2 Peer Review and Feedback
  • Presentation:
    • Students present their final projects to the class, showcasing their Power BI solutions.
  • Feedback Session:
    • Peers and instructors provide constructive feedback on each project.
  • Improvement:
    • Incorporating feedback to enhance the final BI solutions.
    • Finalizing the projects for portfolio inclusion or real-world application.
  • 10.3 Course Recap and Q&A
  • Review of Key Concepts:
    • Summarizing the main topics covered throughout the course.
  • Open Q&A: Addressing any remaining questions or clarifications.
  • Next Steps: Guiding students on further learning resources and certifications in Power BI and related fields.
  • 10.4 Practical Exercise:
  • Complete the final project and prepare a presentation.
  • Participate in peer reviews and apply feedback to improve the project.
  • Recommended Resources
  • Books:
    • The Definitive Guide to DAX by Marco Russo and Alberto Ferrari
    • Introducing Microsoft Power BI by Alberto Ferrari and Marco Russo
  • Practice Datasets:
  • Assessment Methods
  • Quizzes: Module-wise quizzes to reinforce learning and assess understanding.
  • Assignments: Practical assignments based on each module to apply concepts.
  • Final Project: Comprehensive business intelligence solution demonstrating all course components.
  • Participation: Active participation in discussions, exercises, and peer reviews.
  • Hands-On Learning:
    • Encourage students to actively participate in practical exercises and projects.
    • Provide real-world scenarios to make learning relevant and engaging.
  • Interactive Sessions:
    • Use live demonstrations to illustrate complex concepts and functionalities.
    • Facilitate group activities and collaborative projects to enhance teamwork skills.
  • Continuous Feedback:
    • Offer regular feedback on assignments and projects to guide student progress.
    • Create an open environment for questions and discussions to address any learning gaps.
  • This detailed module-wise syllabus ensures that students will progressively build their skills in Microsoft Power BI, culminating in the ability to create and manage sophisticated business intelligence solutions effectively. The combination of theoretical knowledge and practical application prepares students for real-world data analysis and decision-making challenges.
  • Sample datasets available within Power BI Desktop.
  • Custom datasets provided by instructors for hands-on practice.
  • Multiple-Choice Questions (MCQs) along with their answers, based on the Microsoft Power BI Business Intelligence Course :-
  • Module 1: Introduction to Microsoft Power BI
  • Q1. What is Power BI primarily used for?
  • a) Word processing
  • b) Data visualization and analysis
  • c) Cloud storage
  • d) Web development
    Answer: b) Data visualization and analysis
  • Q2. Which of the following is NOT a component of Power BI?
  • a) Power BI Desktop
  • b) Power BI Service
  • c) Power Query
  • d) PowerPoint
    Answer: d) PowerPoint
  • Q3. What is the main purpose of Power BI Mobile?
  • a) Create new Power BI reports
  • b) Access and interact with reports and dashboards on mobile devices
  • c) Perform advanced data transformations
  • d) Develop custom visuals
    Answer: b) Access and interact with reports and dashboards on mobile devices
  • Module 2: Connecting to Data Sources
  • Q4. Which tool in Power BI is used to transform and clean data before loading it into the report?
  • a) Power Query
  • b) Power BI Service
  • c) Power Map
  • d) Power BI Gateway
    Answer: a) Power Query
  • Q5. What type of data source is NOT supported by Power BI for direct connection?
  • a) Excel files
  • b) SQL Server
  • c) CSV files
  • d) Microsoft Word files
    Answer: d) Microsoft Word files
  • Q6. Which transformation operation is typically used in Power Query to remove redundant rows?
  • a) Merge Queries
  • b) Pivot Data
  • c) Remove Duplicates
  • d) Unpivot Data
    Answer: c) Remove Duplicates
  • Module 3: Data Modeling
  • Q7. In Power BI, what does DAX stand for?
  • a) Data Access Expressions
  • b) Data Analysis Expressions
  • c) Data Analytics Exchange
  • d) Data Application Execution
    Answer: b) Data Analysis Expressions
  • Q8. Which of the following is a key feature of calculated columns?
  • a) They are created in the data source.
  • b) They are computed in real-time as data is refreshed.
  • c) They are created using DAX and stored in the model.
  • d) They automatically update when visualized.
    Answer: c) They are created using DAX and stored in the model.
  • Q9. What type of relationship is created when one table’s column can have multiple matches in another table?
  • a) One-to-One
  • b) One-to-Many
  • c) Many-to-One
  • d) Many-to-Many
    Answer: d) Many-to-Many
  • Module 4: Creating Visualizations
  • Q10. Which visualization in Power BI is best suited for displaying trends over time?
  • a) Pie Chart
  • b) Line Chart
  • c) Scatter Plot
  • d) Donut Chart
    Answer: b) Line Chart
  • Q11. How can you add interactivity to a Power BI report, allowing users to filter data by clicking on visuals?
  • a) Add conditional formatting
  • b) Enable slicers and cross-filtering
  • c) Use dynamic visuals
  • d) Create custom measures
    Answer: b) Enable slicers and cross-filtering
  • Q12. Which map visualization is ideal for showing geographical data with boundaries such as countries or states?
  • a) Heat Map
  • b) Bubble Map
  • c) Filled Map
  • d) Line Map
    Answer: c) Filled Map
  • Module 5: Advanced Data Analysis
  • Q13. What DAX function can you use to create year-over-year comparisons in Power BI?
  • a) CALCULATE
  • b) TOTALYTD
  • c) DATEADD
  • d) SAMEPERIODLASTYEAR
    Answer: d) SAMEPERIODLASTYEAR
  • Q14. What is the primary benefit of creating “What-If Parameters” in Power BI?
  • a) Filtering data based on specific conditions
  • b) Forecasting future trends
  • c) Analyzing different business scenarios dynamically
  • d) Creating real-time data updates
    Answer: c) Analyzing different business scenarios dynamically
  • Q15. When using the CALCULATE function, which term refers to the transition from row context to filter context in DAX?
  • a) Filter propagation
  • b) Context transition
  • c) Row modification
  • d) Data manipulation
    Answer: b) Context transition
  • Module 6: Dashboards and Storytelling
  • Q16. Which of the following is NOT a recommended practice for designing effective dashboards in Power BI?
  • a) Using a clear and intuitive layout
  • b) Overloading the dashboard with visuals
  • c) Ensuring visual consistency
  • d) Balancing aesthetics with functionality
    Answer: b) Overloading the dashboard with visuals
  • Q17. What Power BI feature allows you to highlight key insights in a report and guide users through the data?
  • a) Custom visuals
  • b) Report filters
  • c) Annotations and callouts
  • d) Hierarchical filtering
    Answer: c) Annotations and callouts
  • Q18. How can you optimize a dashboard for viewing on mobile devices?
  • a) Reduce the number of visuals
  • b) Create a responsive layout using the Mobile View in Power BI
  • c) Use only text-based visuals
  • d) Disable interactivity on mobile dashboards
    Answer: b) Create a responsive layout using the Mobile View in Power BI
  • Module 7: Sharing and Collaboration
  • Q19. What is the purpose of publishing reports to Power BI Service?
  • a) To design new visualizations
  • b) To collaborate with colleagues and share insights
  • c) To add data to Power BI Desktop
  • d) To create custom visuals
    Answer: b) To collaborate with colleagues and share insights
  • Q20. Which of the following is required to set up scheduled refresh in Power BI Service?
  • a) SQL Server integration
  • b) Power BI Gateway
  • c) Power Query integration
  • d) DAX integration
    Answer: b) Power BI Gateway
  • Q21. What is the main use of Power BI apps within an organization?
  • a) To create custom visuals
  • b) To package and distribute dashboards and reports
  • c) To transform data using Power Query
  • d) To perform advanced calculations
    Answer: b) To package and distribute dashboards and reports
  • Module 8: Power BI Administration and Security
  • Q22. Which feature of Power BI allows you to restrict access to data based on a user’s role?
  • a) Row-Level Security (RLS)
  • b) Sensitivity Labels
  • c) Field-level encryption
  • d) Report Filters
    Answer: a) Row-Level Security (RLS)
  • Q23. What is the purpose of sensitivity labels in Power BI?
  • a) To enhance report interactivity
  • b) To classify and protect sensitive data
  • c) To enable drill-through reports
  • d) To speed up data refresh
    Answer: b) To classify and protect sensitive data
  • Module 9: Power BI Integration and Extensibility
  • Q24. Which Microsoft service can be used to automate workflows and tasks triggered by data events in Power BI?
  • a) Power Automate (Flow)
  • b) Power Apps
  • c) Excel Macros
  • d) Azure Functions
    Answer: a) Power Automate (Flow)
  • Q25. Which of the following allows embedding Power BI reports into external web applications?
  • a) Power Query
  • b) Power BI Report Server
  • c) Power BI Embedded
  • d) Power Pivot
    Answer: c) Power BI Embedded
  • These questions cover various aspects of the course, testing both theoretical understanding and practical knowledge of Microsoft Power BI.
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