This interactive School System Dashboard was developed using Power BI with backend data queries written in SQL. It provides school administrators a centralized view of key academic, financial, and operational metrics. 

🛠️ Tools & Technologies Used

• Power BI: For data visualization, DAX measures, slicers, and layout design.

• SQL: For data extraction, transformation, and aggregation from relational databases.

• DAX: To calculate KPIs such as attendance rate, grade distributions, and fee trends.
  
  

📌 Key Features

• 🔹 KPI Cards (Top Panel)

• Total Students: 100

• Total Fees: 3M

• Total Teachers: 20
  
  

🔹 Class Attendance Rate (Gauge Visual)

• Shows average attendance: 47.33%

• Built using a calculated DAX measure.
  
  

🔹 Student Performance by Grade (Bar Chart)

• Grade-wise student percentage:

• A: 23%, B: 22%, C: 21%, D: 17.5%, F: 16.5%

• Enables quick performance benchmarking.
  
  

🔹 Monthly Fee Collection Trend (Line Chart)

• Visualizes fee income from January to June.

• Highlights financial fluctuations and forecasting needs.
  
  
  

• 🔹 Enrollment by Semester (Bar Chart)

• Tracks student enrollment across Fall, Spring, and Summer.

• Fall shows the highest enrollment (79 students).

🔹 Student Status Distribution (Pie Chart)

• Attendance breakdown:

• Present: 158 (52.67%)

• Absent: 142 (47.33%)
  
  

🔹 Dynamic Table (With Filters)

• Displays detailed student data, including:

• Name, Credits, Department, Grade, Enrollment Year

• Interactive filters for Department and Year enable drill-down analysis.
  
  

💡 Value Delivered

• Helps stakeholders monitor student attendance, academic performance, and fee collection trends.

• Supports data-driven decisions on staffing, academic support, and financial forecasting.

• Provides filterable, real-time insights with drill-through capabilities.
  
  

🧠 Skills Demonstrated

• Data Modeling & Relationship Management in Power BI

• SQL Querying for Optimized Data Retrieval

• KPI and DAX Calculations

• Dashboard Interactivity with Slicers

• Clean, modern UI design for business users

🗂️ Use Case

Ideal for school principals, administrative staff, or education boards to track institutional performance and operational efficiency in real time.

This interactive Power BI dashboard provides a comprehensive view of company-wide financial performance, enabling stakeholders to monitor revenue, expenses, and profitability trends across business units and scenarios.

Key features include:

• ✅ Dynamic KPI Cards displaying Total Revenue, Expenses, Net Profit, and Profit Margin
  
  

• ✅ Top Performing Accounts Analysis for identifying leading revenue and cost drivers
  
  

• ✅ Monthly Business Unit Contributions via stacked column visuals
  
  

• ✅ Profitability Distribution using pie charts and treemaps by business unit
  
  

• ✅ Trend Analysis showing monthly and yearly financial performance
  
  

• ✅ Scenario Comparison (Actuals, Budget, Forecast)
  
  

• ✅ Interactive Slicers for Month, Year, Scenario, Account, and Business Unit
  
  

• ✅ Reset Button for clearing all filters with one click
  
  

• ✅ Dynamic Titles that reflect selected filter context (e.g., “Amount by June”)
  
  

🎯 Tools Used: Power BI, DAX, Power Query
📊 Skills Demonstrated: Data modeling, KPI design, DAX measures, interactive storytelling, UX layout, time intelligence, visual hierarchy

The goal of this dashboard is to provide a clear and interactive visual summary of an artwork collection dataset. It enables users to explore key insights such as total artworks, artworks on view, popular artists, gender distribution of artists, departmental contributions, and historical trends. 

📊 Key Features

1. KPI Cards

   • Total Artworks: Displays the total number of artworks (1,091).

   • Total On View: Shows artworks currently displayed (72).

2. Year Range Filter

   • Interactive slider allows users to filter artworks based on creation year (from 1932 to 2024).

3. Dropdown Filters

   • Department & OnView: Let users narrow down data dynamically by department or display status.

4. Artwork by Artist

   • Horizontal bar chart showing the top contributing artists, led by Robert Frank (54 artworks).

5. Artwork Over Time

   • Line graph illustrating how the number of artworks evolved over years, identifying peaks and declines.

6. Top 10 Artist (Count View)

   • Vertical bar chart includes total artworks per artist, including a high number of unclassified ("Blank") entries, pointing to potential data quality issues.

7. Gender Distribution

   • Donut chart visualizing the gender breakdown of artists. This shows a dominance of male artists, with a smaller portion of female artists.

8. Artworks by Department

   • Column chart showing the number of artworks per department. The top three departments:

     • Painting (455)

     • Drawing (266)

     • Photography (195)
       
       

🎯 Skills Demonstrated

• Power BI dashboard layout design and customization

• Use of DAX for KPIs and measures

• Interactive filtering with slicers and dropdowns

• Insightful visual storytelling using appropriate charts

• Data quality awareness (e.g., handling blank artist names)

💡 Impact

This dashboard provides museum staff or art collection managers with a comprehensive and interactive tool to monitor and analyze artwork collections, artist contributions, and exhibition status, supporting strategic decision-making in curation and display planning.

This project showcases a professional HR IT Dashboard built using Microsoft Power BI, a leading data visualization tool. The dashboard provides HR and IT departments with a comprehensive, interactive view of workforce metrics, employee performance, ticket management, and financial transactions. It's designed to support data-driven decision-making and enhance operational visibility across departments. 

🔑 Key Features:

• Executive Summary KPIs: Displays total employees, spend, tickets, and transactions at a glance.

• Department-Level Analysis: Visual breakdowns of average salaries, employee performance ratings, and job role distributions for HR, IT, and Finance.

• IT Service Monitoring: Tracks tickets by technician, priority, and status to evaluate help desk efficiency.

• Financial Insights: Highlights monthly spend trends, top vendors, and transaction types (e.g., procurement, invoices).

• Interactive Filters: Enables dynamic filtering by department, priority level, and transaction category for real-time exploration.

• Visual Best Practices: Clear, well-organized visuals that are easy to interpret for both technical and non-technical stakeholders.

📐 Data Modeling:

• Built a star schema with fact tables for:

  • Employees

  • Transactions

  • Tickets

• Connected to dimension tables like Departments, Positions, Vendors, and Priority Levels.

• Used DAX measures to calculate totals, averages, and trends (e.g., average salary, ticket counts by status).

🧼 Data Cleaning & Transformation:

• Performed data cleansing using Power Query, including:

• Removing nulls and duplicate entries.

• Standardizing categorical fields (e.g., department names and performance ratings).

• Formatting salary and spending data into readable currency values.

• Ensured clean joins between tables through key normalization and data type alignment.

The project is a Human Resources Dashboard, a popular data visualization tool. Tableau is well-suited for building interactive dashboards like this, which help HR teams analyze workforce data efficiently.

Key Features of the HR Dashboard:

1. Interactive Design: Tableau allows users to filter and drill down into specific categories (e.g., by department, age group, location, etc.).

2. Comprehensive Metrics:

   • Headcount Metrics:

     • Active Employees: Displays the total number of current employees.

     • Hired vs. Terminated: Tracks hiring and termination trends over time.

   • Demographics:

     • Age Groups and Gender distributions provide insights into workforce diversity.

   • Education Levels: Shows the highest level of education attained by employees.

   • Education vs. Performance: Correlates education levels with performance ratings to identify trends.

   • Age vs. Salary: Highlights pay distribution across different age groups and roles.

3. Department Overview:

   • Employee count and termination rate by department.

4. Location Analysis:

   • Percentage of employees working in headquarters vs. branches.

   • Geographical distribution visualized through a map.

5. Role-Based Metrics:

   • Scatter plots or detailed salary data by job title (e.g., IT Manager, Finance Manager).

The Sales Performance Dashboard in Looker provides a dynamic and interactive visualization platform for tracking key sales metrics, analyzing trends, and monitoring performance across regions and products. It enables data-driven decision-making for enhanced business growth. 

This Tableau dashboard visualizes sales performance across regions, categories, and periods for a sample superstore. It includes:

1. Regional Analysis: Highlighting sales trends and total revenue across the West, South, East, and Central regions with line charts and annotated totals.

2. Geographical Insights: A map showcasing sales distribution using bubble size to indicate revenue intensity in various locations.

3. Category-Level Breakdown: Bars and scatter plots presenting sub-category sales data and their trends over time.

4. Segment Performance: Revenue contribution segmented by consumer, corporate, and home office clients.

5. Product-Level Details: Individual product IDs ranked by sales to highlight top-performing products.

6. Timeline Trends: Sales patterns are visualized yearly for key sub-categories.

This dashboard was designed using Tableau to enable an interactive exploration of sales metrics, fostering strategic decision-making and insights into areas for improvement.

The Web Marketing Dashboard in Tableau is an interactive visualization tool designed to track and analyze key performance metrics for digital marketing campaigns, including website traffic, conversion rates, and audience engagement. It provides actionable insights to optimize marketing strategies. 

This Web Marketing Dashboard is designed in Tableau to provide key insights into website performance metrics. It features:

1. High-Level Metrics:

   • Total sessions by year: 418,062

   • Total page views: 855,052

   • Average page load time: 71.61 seconds

   • Time spent on pages: 98.49 seconds

2. Device-Specific Breakdown:

   • Distribution of page views across desktop (292,287), mobile (113,691), and tablet (12,084) users.

3. Monthly Trends:

   • Line chart visualizing session trends over months, with significant dips and peaks, highlighting August as the highest traffic month (49,167 sessions).

4. Engagement Insights:

   • This is a bar chart displaying the average time spent on pages per month, with a peak in August (30.141 seconds).

5. Process and Artefacts:

   • Data was extracted from web analytics tools, cleaned, and integrated into Tableau.

   • Interactive filters and visualizations were built to enable stakeholders to effectively explore user behavior and website performance trends.

This dashboard gives decision-makers actionable insights to improve user engagement and optimize marketing strategies.

The Super Store Sales Dashboard in Tableau is an interactive visualization tool designed to track and analyze key performance metrics for digital marketing campaigns, including website traffic, conversion rates, and audience engagement. It provides actionable insights to optimize marketing strategies. 

This project showcases a SuperStore Sales Dashboard built in Tableau to visualize and analyze sales performance across regions, categories, and states over time. The process involved:

1. Data Preparation:

   • Cleaning and organizing the sales dataset to ensure accuracy in the analysis.

   • Structuring the data to categorize by region, category, year, and state for detailed insights.

2. Dashboard Design:

   • Selecting appropriate visualizations like bar charts, line graphs, bubble charts, and geographic maps to present data effectively.

   • Employing interactivity to enable drill-down analysis.

3. Key Artefacts Created:

   • Region by Profit: A horizontal bar chart showing profit distribution across regions.

   • Year by Sales and Profit: A dual-axis chart for comparing yearly sales trends against profit margins.

   • Region by Sales: A bubble chart visualizing sales contribution by region.

   • Category by Sales and Profit: A scatterplot breaking down sales and profit by product category.

   • State by Quantity and Sales: A map overlay to analyze quantity sold and sales performance by location.

The dashboard serves as an insightful tool for understanding business performance and guiding strategic decisions.

This project presents an enhanced Super Store Dashboard built in Tableau, designed to provide a detailed analysis of sales, profits, discounts, and quantities across various dimensions like state, product categories, and time. The process and key artifacts include:

Process:

1. Data Preparation:

   • Cleaned and structured the dataset for seamless integration with Tableau.

   • Focused on creating measures and dimensions to analyze sales performance by state, product type, and time period.

2. Dashboard Design:

   • Developed visually distinct charts and widgets to highlight key metrics.

   • Ensured interactive functionality to support dynamic data exploration.

3. Insights Creation:

   • Used forecasting models to predict future sales trends.

   • Incorporated advanced visualization techniques for deeper insights.

Artifacts Created:

• KPI Tiles: Highlights for total profit, discount, sales, and quantity.

• Bullet Chart: Displays profit distribution across states.

• Scatter Plot: Correlates sales and profit by product category.

• Donut Chart: Breaks down sales by product type.

• Radial Bar Chart: Top 10 states ranked by sales.

• Forecasting Chart: Predicts future sales and profit trends.

• Pareto Chart: Highlights cumulative sales contribution by-products.

• Map Visualization: Displays sales and quantities by geographical regions.

This dashboard enables business stakeholders to quickly identify trends, uncover profit opportunities, and make data-driven decisions to enhance business growth.

This DS Salary Dashboard provides a comprehensive visualization of salary trends and distributions in the field of Data Science, segmented by job title, experience level, employment type, company size, and geography. Here's an overview of the project:

Process:

1. Data Cleaning and Preparation:

   • Organized salary data by key dimensions like job titles, countries, experience levels, and company sizes.

   • Ensured data consistency for accurate analysis.

2. Dashboard Design:

   • Selected visualizations such as maps, pie charts, and bar graphs to present data effectively.

   • Incorporated interactivity to allow users to explore salary trends dynamically.

3. Insights Extraction:

   • Focused on highlighting variations in salaries across regions and experience levels.

   • Identified top locations and employment types contributing to higher salaries.

Artifacts Created:

• KPI Tiles: Displays key metrics like average salaries by employment type, job title, and company size.

• Pie Charts: Breakdowns for experience levels, employment types, and company sizes.

• Map Visualization: Highlights average salaries by country.

• Bar Charts: Showcases top 10 residence locations and salaries by experience level.

• Scatter Plot: Displays salary ranges for various experience levels.

This dashboard empowers professionals and organizations to analyze compensation trends, identify high-paying regions and roles, and make informed decisions about career or hiring strategies.

This Dashboard provides an interactive analysis of data submissions, user feedback, and course participation trends. It is designed for dynamic exploration of key metrics over various time periods and categories.

Process:

1. Data Organization:

   • Structured data to include dimensions like Date, Month, Year, Submission Count, Feedback Categories, and Course Names.

   • Prepared metrics for user feedback categorized by usefulness ratings (e.g., Extremely Useful, Somewhat Useful).

2. Dashboard Design:

   • Created visualizations to highlight submission patterns, feedback trends, and course-specific insights.

   • Implemented filters for date, month, year, and course names to enhance interactivity.

Artifacts Created:

• Line Chart: Shows the count of submissions by feedback categories over time, highlighting trends in user feedback.

• Bar Charts:

  • Displays submission counts for different course categories.

  • Highlights participation by live, self-paced, or other course formats.

• Pie Chart: Represents feedback distribution across usefulness ratings.

• Filter Panels: Allows filtering by Date, Month, Year, and Course Name for detailed exploration.

Insights:

This dashboard empowers stakeholders to:

• Analyze user engagement and feedback trends over time.

• Identify popular courses and participation modes.

• Make data-driven decisions for improving course offerings and user satisfaction.

It is optimized for clear visualization and user-friendly interaction.