Tata Data Visualization and Cleaning Project

📊 Project Overview

This project is part of the Tata Data Visualisation: Empowering Business with Effective Insights virtual experience program on Forage.
I performed data cleaning using Python (Pandas) and created business dashboards using Power BI to analyze the Online Retail Dataset.

The project aims to deliver actionable insights for business decision-makers by leveraging clean data and meaningful visualizations.

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🛠️ Tools & Technologies Used

• Python (Pandas) for Data Cleaning
• Power BI for Data Visualization

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📂 Repository Contents

File / Folder	Description
data clean.py	Python script for data cleaning
Online_Retail_Cleaned.zip	Cleaned dataset in ZIP format
Online Retail Data Set.zip	Original dataset in ZIP format
Empowering_Insights_Tata_Course_Project.pbix	Power BI Report file
Dashboard_Overview.jpg	Dashboard overview screenshot
Global_Sales_Overview_Excluding_UK.jpg	Power BI visual screenshot
Product_Performance_Overview.jpg	Product performance dashboard
page_information.jpg	Dashboard page information overview
popup_filters.png	Power BI filters popup view
README.md	Project documentation

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📝 Project Summary (As per Program Guidelines)

This project was developed following the core objectives of the Tata Data Visualisation: Empowering Business with Effective Insights program on Forage.

I performed comprehensive data cleaning, handling missing values, removing invalid rows, and ensuring data quality before visualization.
The Power BI dashboard contains multiple pages with advanced interactivity features like page navigation buttons and slicers for easy analysis.

Key Highlights:

• On Page 1, I provided a global sales overview (including the UK).
• On Page 2, I showcased a global sales overview excluding the UK, as per the program's recommendation.
• I also checked for null values, removed duplicates, handled invalid rows such as:
  • Invalid Rows (Quantity < 1): 10,624
  • Invalid Rows (UnitPrice < 0): 2
• The cleaned dataset was used for creating actionable business insights through Power BI visualizations.

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🧹 Data Cleaning Summary

Before Cleaning:

Initial Null Values:
InvoiceNo           0
StockCode           0
Description      1454
Quantity            0
InvoiceDate         0
UnitPrice           0
CustomerID     135080
Country             0

Number of Duplicate Rows: 5268
Total Rows Before Cleaning: 541909

Invalid Rows (Quantity < 1): 10624
Invalid Rows (UnitPrice < 0): 2

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After Cleaning:

Missing Values After Cleaning:
InvoiceNo      0
StockCode      0
Description    0
Quantity       0
InvoiceDate    0
UnitPrice      0
CustomerID     0
Country        0

Total Rows After Cleaning: 392732

Invalid Rows (Quantity < 1) After Cleaning: 0
Invalid Rows (UnitPrice < 0) After Cleaning: 0

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✅ The data cleaning process ensured that all missing values, invalid entries, and duplicates were handled before moving to the visualization phase.

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📸 Power BI Dashboard Snapshots

I also implemented Page Navigation Buttons within the dashboard to allow smooth navigation between different report pages.
This improves the interactivity and user experience by helping users switch between insights easily.

— Global Sales Overview

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— Filter Section Overview

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🌍 Page 2 — Global Sales Overview (Excluding UK)

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📦 Page 3 — Product Performance Overview

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ℹ️ Page 4 — Page Information

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These dashboards present key insights like revenue trends, top-performing countries, customer performance, and global sales distribution.

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📚 What I Covered in This Project

In this simulation, I:

• ✅ Completed a project focused on creating data visualizations for Tata Consultancy Services (TCS)
• ✅ Analyzed data and designed visuals to support executive-level decision-making
• ✅ Learned how professionals handle large datasets and transform them into actionable business insights for leaders like the CEO and CMO
• ✅ Gained practical experience in data cleaning, data visualization, and business storytelling

This experience sharpened my skills in data analysis, Power BI, and communicating insights with impact.

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🏆 Achievements

• ✅ Successfully cleaned and validated a real-world retail dataset with over 540,000 records
• ✅ Identified and handled missing values, invalid rows, and duplicate entries
• ✅ Designed a multi-page interactive Power BI dashboard with slicers, filters, and navigation buttons for seamless analysis
• ✅ Delivered visual insights on sales trends, top-performing countries, and key customers
• ✅ Presented a comprehensive global sales overview with region-specific insights (including/excluding UK)
• ✅ Enhanced business storytelling through professional data visualization techniques

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📥 How to Use This Project

• 🔹 Clone or download the repository
• 🔹 Extract datasets from ZIP files
• 🔹 Open data clean.py for Python data cleaning steps
• 🔹 Open .pbix file in Power BI Desktop to explore dashboards

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📢 Acknowledgment

This project was completed as part of the Tata Data Visualisation Virtual Experience Program offered by Forage.

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📜 Certificate of Completion

This project was completed as part of the Tata Data Visualisation: Empowering Business with Effective Insights virtual experience on Forage.

📄 View Certificate

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👨‍💻 Author

Bikramadittya Nandan

• 🌐 LinkedIn Profile
• 🐙 GitHub Profile

Feel free to connect with me for collaborations, feedback, or discussions on data analytics projects!

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