Power BI Lab Assignments with Reference Articles

 

Power BI Lab Assignments with Reference Articles

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Assignment 1: SampleSuperStore Dashboard

Objective:

To analyze business performance using sales, profit, and customer data from a retail store.

Problem Statement:

Retail companies often struggle to identify underperforming regions, products, and customer segments. The goal of this dashboard is to visualize key business metrics like sales, profit, discount, and shipping mode by region and category to help decision-makers optimize operations.

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Assignment 2: Result Analysis Dashboard

Objective:

To design an academic performance monitoring dashboard for institutional analysis.

Problem Statement:

Educational institutions require a streamlined view of students’ results across semesters, subjects, and courses. This dashboard will visualize pass/fail percentages, top scorers, subject-wise performance, and trends over time to support academic decision-making.

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Assignment 3: COVID-19 Dashboard

Objective:

To track the impact of COVID-19 across countries/states through real-time analytics.

Problem Statement:

During a pandemic, it is critical to monitor case trends, mortality rates, recovery status, and testing rates. This dashboard will help in visualizing confirmed cases, recoveries, deaths, and vaccination data using interactive maps and charts.

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Assignment 4: World Population Dashboard

Objective:

To explore global population trends by country, age group, and gender using interactive visuals.

Problem Statement:

Understanding demographic changes is essential for planning global resources and policy-making. This dashboard will display population growth, density, gender ratio, and age group distributions to provide insights into regional demographics.

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Assignment 5: Customer Spending Behavior Analysis

Objective:

To analyze customer spending patterns based on product categories, purchase frequency, and regions.

Problem Statement:

Businesses need to understand customer purchasing behavior to create personalized marketing strategies. This dashboard will help identify high-value customers, seasonal trends, and frequently purchased product categories through sales data visualization.

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Assignment 6: Cyber Crime Trend Analysis

Objective:

To create a visual analytical report of cybercrime incidents categorized by year, state, and crime type.

Problem Statement:

The increasing number of cybercrimes calls for a visual representation of crime trends to support prevention and law enforcement strategies. This dashboard aims to track cybercrime types such as fraud, identity theft, hacking, and more across different regions and years.

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Assignment 7: Crime Against Children Analysis

Objective:

To develop a dashboard showcasing reported crimes against children, segmented by region, crime type, and year.

Problem Statement:

Crimes against children have become a major social concern. The aim of this dashboard is to visualize patterns, highlight high-risk areas, and provide actionable insights to support child protection initiatives by analyzing national crime datasets.

Assignment 8: Geospatial and Demographic Analysis of Indian Census Data Using Power BI via Google Drive Integration

Objective:
To analyze India's demographic and geographic distribution by leveraging Power BI for meaningful insights into population, settlements, and resource density using census data hosted on Google Drive.

To effectively plan resources and infrastructure, policymakers need to analyze population distribution, settlement types, and density across Indian states. This project guides students to use Power BI to connect live census data stored on Google Drive, transform the dataset using Power Query, and create a visual demographic report.

Assignment 9: Weather Analysis and Forecasting in Power BI

Problem Statement:Accurate weather forecasting remains a challenge due to the dynamic and complex nature of atmospheric conditions. This project aims to analyze historical weather data to identify key patterns and build predictive models that can forecast weather parameters such as temperature, humidity, and precipitation with greater reliability.

Assignment 10: Analyze Historical Stock Data of Tesla Stock in Power BI

Problem Statement:  Analyze historical stock data to extract actionable insights about price behavior, volatility, trading activity, and relationships between price and volume. Students will transform and normalize the data, create analytical measures and visuals, and build an interactive Power BI report using both basic and advanced visuals (decomposition tree, drillthrough, bookmarks, selection pane, gauge, custom tooltips, Smart Narrations).

Assignment 11 : Mini Project Based on the dataset prepared by you

Assignment 12 : Power BI Project on Indian Kids Screen Time

Problem Statement : To analyze the impact of screen time on children in India, focusing on their primary devices, educational-to-recreational balance, and associated health issues, and to derive insights for parents, educators, and policymakers using Power BI visualization and analytics

Assignment 13: Power BI Project On BHEL Stock Analysis

Problem Statement:

Analyze BHEL’s stock price trends and trading behavior over time. Identify patterns in daily price changes, volatility, and trading volume. Develop insights through advanced calculations and visualizations, including moving averages, cumulative returns, gain/loss classification, and forecast future stock prices to support informed investment decisions.

Dataset Description:

The dataset contains historical stock data for BHEL, including daily records of Open, High, Low, Close, Adjusted Close prices, and trading Volume from 2020 onwards. Each row represents one trading day, capturing market movements and trading activity.

Assignment 14: Power BI Project on Healthcare Dataset

Problem Statement

In today’s data-driven environment, organizations across industries are challenged not only to collect vast amounts of data but also to transform it into actionable insights that support strategic decision-making. Traditional reporting techniques often fall short in providing interactive, real-time, and predictive capabilities. As a result, decision-makers struggle with fragmented dashboards, static reports, and limited forecasting tools that hinder proactive business planning.

Columns:

• Name, Age, Gender, Blood Type, Medical Condition, Date of Admission, Doctor, Hospital, Insurance Provider, Billing Amount, Room Number, Admission Type, Discharge Date, Medication, Test Results

Assignment 15: Power BI Project on  IPL Auction Dataset

Problem Statement

The Indian Premier League (IPL) franchises often face the challenge of building a balanced team while staying within their budget constraints. Teams must evaluate players based on their roles (Batsman, Bowler, All-Rounder, Wicket Keeper), nationality (Indian vs Overseas), and price paid during the auction to optimize performance.

This dataset provides details of a few players purchased by Chennai Super Kings (CSK), including their name, nationality, type, price, and team. The key problem is to analyze how the composition of players affects the team structure and to explore insights such as:

• Distribution of Indian vs Overseas players.

• Balance of roles (Batsman, All-Rounder, Wicket Keeper, etc.).

• Price allocation strategy across player categories.

• Identifying potential areas of overspending or underspending.

Assignment 16 : World Crime Index 

Problem Statement

Crime and safety are critical concerns that directly affect the quality of life, economic growth, and societal development across cities worldwide. This dataset provides comparative insights into cities with high crime rates and low safety indexes. Analyzing this data can help policymakers, researchers, and urban planners identify vulnerable regions, understand crime patterns, and propose actionable strategies to improve urban safety and governance.

Dataset Description

• Rank – Position of the city based on crime index (1 = highest crime risk).

• City – Name of the city under analysis.

• Country – Country to which the city belongs.

• Crime Index – A numerical measure (0–100) reflecting the overall level of crime in the city (higher value = more crime).

• Safety Index – A numerical measure (0–100) representing how safe the city is perceived (higher value = safer).

Assignment 17: Indian School Analysis

Problem Statement

Educational development is one of the critical indicators of a nation’s growth. Despite significant policy interventions in India, disparities persist across states, gender, and different educational levels. This dataset provides information on Gross Enrolment Ratios (GER) of boys, girls, and total students at primary, upper primary, secondary, and higher secondary levels across Indian States and Union Territories for multiple years.

The challenge is to analyze trends, identify gaps in enrolment across gender and states, and evaluate whether progress has been uniform. This study will help policymakers, educators, and researchers understand:

• Gender disparities in school education.

• State-wise differences in educational development.

• The progression from primary to higher secondary levels.

• Year-wise changes and the effectiveness of education policies.

By leveraging this dataset, data-driven insights can be generated to improve policy decisions, reduce dropouts, and ensure equitable access to education.

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Dataset Description

• Source: Indian School Education Statistics (Government of India).

• Scope: Covers Gross Enrolment Ratios (GER) across different school levels.

• Granularity: Yearly data for each State/UT.

Features

1. State_UT – Name of the State or Union Territory.

2. Year – Academic year of data (e.g., 2012-13, 2013-14, etc.).

3. Primary_Boys – GER of boys at the primary level.

4. Primary_Girls – GER of girls at the primary level.

5. Primary_Total – Combined GER for boys and girls at the primary level.

6. UpperPrimary_Boys – GER of boys at the upper primary level.

7. UpperPrimary_Girls – GER of girls at the upper primary level.

8. UpperPrimary_Total – Combined GER at the upper primary level.

9. Secondary_Boys – GER of boys at the secondary level.

10. Secondary_Girls – GER of girls at the secondary level.

11. Secondary_Total – Combined GER at the secondary level.

12. HrSecondary_Boys – GER of boys at the higher secondary level.

13. HrSecondary_Girls – GER of girls at the higher secondary level.

14. HrSecondary_Total – Combined GER at the higher secondary level.