Case Studies: Snapdeal & Indigo Airlines

(Excel for Data Cleaning & Formatting)

Data cleaning is not just a theoretical concept—leading companies like Snapdeal and Indigo Airlines rely heavily on Excel-based tools for managing their day-to-day data operations. These case studies illustrate how such companies utilize Excel to solve real-world data issues.

Snapdeal: Managing Product & Vendor Data

Background:

As an e-commerce platform, Snapdeal handles data from thousands of sellers and millions of products. Data inconsistency across product listings (like wrong prices, missing images, or category mismatches) directly impacts customer experience and trust.

Excel in Action:

• Data Consolidation: Snapdeal uses Excel to import CSV sheets from multiple vendors. They clean and unify the format using Text-to-Columns, Trim, and Find & Replace tools.

• Removing Duplicates: Duplicate product listings are removed using Remove Duplicates on SKU or Product ID fields.

• Handling Nulls: Missing product attributes like weight or color are flagged using conditional formatting and handled using IF formulas to insert default values.

• Validation Rules: Data validation is applied to price columns and category dropdowns to avoid manual errors.

Impact:

Improved accuracy in product listings led to reduced return rates and higher customer satisfaction.

Indigo Airlines: Passenger & Booking Data Cleaning

Background:

Indigo processes massive amounts of passenger data daily for bookings, cancellations, and flight schedules. Clean and accurate data is critical for operations, reporting, and regulatory compliance.

Excel in Action:

• Null Checks in Passenger Records: Using formulas like =ISBLANK() and filters to identify missing names, IDs, or contact numbers.

• Date Formatting: Ensuring consistency in travel and booking dates using Format Cells and TEXT() functions.

• Error Flagging: Detecting incorrect PNR numbers or duplicate entries with COUNTIF and Conditional Formatting.

• Pivot Tables: Used to analyze cancellations, check-in data, and segment passengers based on flight routes or booking sources.

Impact:

Cleaner datasets resulted in smoother boarding processes, improved compliance with aviation regulations, and better reporting for route planning.

Key Learnings for Students

• Excel is still a powerful tool for initial data cleaning before data is pushed into advanced BI or cloud platforms.

• Data integrity at the ground level (like vendor product listings or passenger records) is the foundation for business success.

• Automation of repetitive cleaning tasks through Excel formulas and tools saves time and reduces human error.