Chapter 1: Power BI – What It Is and How It Works

Chapter 1: Introduction to Power BI

1. What is Power BI?

Power BI is a business analytics tool created by Microsoft. It helps you connect to data, clean it, analyze it, and create interactive reports and dashboards. Power BI turns raw data into meaningful insights.

2. Why Do We Use Power BI?

• To visualize data in the form of charts, tables, and dashboards.
• To make data-driven decisions.
• To combine data from multiple sources like Excel, SQL, web data, etc.
• To share reports with teams or clients easily.
• To refresh dashboards automatically.

3. Components / Parts of Power BI

Power BI has 3 main components:

a) Power BI Desktop

A Windows application used to build reports. You can connect to data, clean data using Power Query, create visuals, and write DAX formulas here.

b) Power BI Service (Online)

A cloud-based platform where you publish reports, create dashboards, share reports, and schedule automatic refresh.

c) Power BI Mobile App

Used to view dashboards and reports on mobile devices.

4. Power BI Workflow (How Power BI Works)

Power BI follows this simple process:

1. Get Data – Import data from Excel, SQL Server, Web, etc.
2. Transform Data – Clean, remove duplicates, merge tables using Power Query.
3. Model Data – Create relationships between tables.
4. Create Visuals – Charts, maps, KPI cards, tables.
5. Publish Report – Upload to Power BI Service.
6. Share Dashboard – Share with others for decision-making.

5. Power BI File Types

• .pbix – Report file created in Power BI Desktop.
• .pbit – Template file (structure without data).

6. Power BI Key Features

• Connects to multiple data sources.
• Provides built-in visuals and custom visuals.
• Supports DAX for advanced calculations.
• Automatic data refresh in Power BI Service.
• Interactive dashboards (filters, slicers, drill-down).

7. Commonly Used Power BI Terms

a) Dataset

The collection of data that you import or connect to in Power BI.

b) Report

A collection of visuals (charts, tables) based on a dataset. A report can have multiple pages.

c) Dashboard

A single-page summary containing visuals pinned from reports.

d) Visualization

A chart, graph, or table that displays your data visually (bar chart, line chart, card, etc.)

e) Data Model

The structure of your tables and their relationships.

8. Example to Understand Power BI

Suppose you have sales data in an Excel file. You import the file into Power BI Desktop, remove empty rows, create a relationship between Sales and Products tables, and build visuals like Sales by Region. Then you publish the report to Power BI Service to share with your team.

9. Summary

Power BI is a complete data analytics tool used to connect, clean, analyze, visualize, and share data. It is simple to learn, powerful for business intelligence, and helpful for decision-making.

Power BI Practical Assignments (Without Lookup Functions)

Assignment 1: Sales Dashboard

Dataset: Sales Table and Product Table

• Import Sales and Product tables.
• Clean data: remove duplicates and blank rows.
• Create relationship between tables.
• Create visuals: Sales by Category, Sales by Region, Monthly Sales, Top 5 Products.
• Create DAX: Total Sales, Total Quantity, Sales Growth Percentage.
• Create and publish a one-page dashboard.

Assignment 2: HR Employee Performance Report

Dataset: Employee Table and Attendance Table

• Load both datasets into Power BI Desktop.
• Clean Attendance table and format date column.
• Create DAX: Total Present Days, Attendance Percentage.
• Create visuals: Attendance % by Department, Age Distribution.
• Create slicers for Department and Employee Type.
• Use conditional formatting to highlight attendance below 70%.

Assignment 3: E-commerce Dashboard

Dataset: Orders, Customers, Products

• Create relationships using CustomerID and ProductID.
• Create DAX: Total Revenue, Total Orders, Average Order Value.
• Create visuals: Revenue by Month, Orders by City, Customer Segmentation.
• Insert Date slicer and create KPI cards.

Assignment 4: Financial Statement Analysis

Dataset: Profit & Loss Excel Sheet

• Import P&L sheet and unpivot monthly columns.
• Create visuals: Expense Breakdown, Income vs Expense.
• Create DAX: Net Profit = Income - Expense.
• Apply conditional formatting for negative values.

Assignment 5: Power Query Data Cleaning

Dataset: Raw Excel File

• Remove duplicate rows.
• Replace errors in dataset.
• Split Full Name into First Name and Last Name.
• Merge Orders and Returns tables.
• Create a custom column: Profit = Sales - Cost.

Assignment 6: School/College Dashboard

Dataset: Students Table

• Calculate Total Marks and Percentage using DAX.
• Create visuals: Marks by Subject, Average Marks by Class, Attendance Trend.
• Enable drill-down for Class → Student.

Assignment 7: Hospital Data Analysis

Dataset: Patients Table and Doctors Table

• Import data tables and create relationships.
• Create visuals: Patient Count by Disease, Age Distribution, Doctor-wise Patients.

Assignment 8: Inventory Management Dashboard

Dataset: Stock and Sales Tables

• Create new column: Current Stock = Opening Stock - Sold Quantity.
• Create Stock Alert Column (Stock < 10 = "Low").
• Create visuals: Low Stock Items, Stock vs Sales.

Assignment 9: Power BI Time Intelligence Practice

Dataset: Sales Table with Date Column

• Create a Date Table.
• Create DAX: YTD Sales, MTD Sales, Previous Year Sales.
• Create visuals comparing current vs previous year.

Assignment 10: Power BI Copilot Tasks

• Ask Copilot to write DAX for Year-to-Date Sales.
• Create a line chart for Monthly Sales using Copilot.
• Ask Copilot to create a summary of the dataset.
• Ask Copilot to generate a Profit Margin measure.
• Compare Copilot's DAX formulas with your own formulas.