DVBI Syllabus

Data Visualization & Business Intelligence with PowerBl (3040233304)

Pre-requisite

• Basic Understanding of MS-EXCEL and Knowledge of database concepts (SQL)

Course Objective

• The syllabus aims to provide a comprehensive understanding of Business Intelligence concepts, Power BI tools, data analysis techniques, visualization methods, and dashboard creation using Power BI Desktop.

Teaching Scheme

Lecture	Theory	Practical	Hours	Credit
3	0	2	5	4

Unit-01 Introduction of BI and Power BI (24%)

• Introduction to Business Intelligence
• Introduction to Power BI
• Traditional BI vs. Power BI, Power BI vs. Tableau vs. QlikView
• Uses of Power BI
• Basic Components of Power BI
• Comparison of Power BI Version
• Data Sources in Power BI Desktop
• Introduction to Power BI Components: Power Query, Power Pivot, Power View, & Power Map

Unit-02 Power BI Desktop and Data Transformation (24%)

• Data Cleaning using Power BI query editor: Importing, cleaning, shaping and Transform data for further analysis
• Handling missing values, duplicates, and outliers
• Skills You will Learn: Data transformation using the query editor
• Data modelling & Managing Data Relationships : Star schema vs. Snowflake schema in Power BI
• Loading Data in Power BI Desktop
• Views in Power BI Desktop

Unit-03 Data Analysis Expression (DAX) (24%)

• Introduction to DAX: Syntax, Data Types, Operators, Creating Calculated Measures and Columns
• DAX Functions: Aggregation & Statistical functions
• Time Intelligence functions (YTD, QTD, MTD, YoY growth)
• Advanced filtering & calculated tables

Unit-04 Data Visualization (28%)

• Creating different visuals: Charts, Tables, Matrixes, Cards, Maps, Visualization Charts in Power BI
• Matrixes and Tables
• Slicers and Map Visualizations
• Modifying Colors in Charts And Visuals, Shapes, Text Boxes, and Images
• Custom Visuals, Page Layout and Formatting, Grouping and Binning
• Power BI Service: Creating a Dashboard
• Configuring a Dashboard, Import Power View and Power Pivot

Practical

1. Import data from CSV/Excel into Power BI and perform data cleaning (remove duplicates, handle missing values).
2. Split columns, merge queries, and create relationships between multiple tables.
3. Create measures for sales analysis (Total Sales, Profit, Average Order Value).
4. Build visuals: Bar chart, Line chart, and Pie chart for sales trends.
5. Create a Map visualization for regional sales distribution.
6. Add slicers and filters to enhance interactivity.
7. Design a dashboard combining multiple visuals (charts, maps).
8. Use DAX to create calculated columns (e.g., Customer Segmentation: High/Medium/Low value).
9. Implement Time Intelligence DAX functions (YoY growth, MTD, QTD).
10. Apply conditional formatting, themes, and company branding in dashboards.
11. Connect Power BI to SQL Database and merge with Excel/CSV data.
12. Apply Grouping and Binning in Power BI to categorize products and segment customers by sales ranges.
13. Create calculated tables and apply advanced DAX filtering techniques for analytical insights.
14. Publish Power BI reports to Power BI Service and create/configure an interactive dashboard.

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