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Data Migration & Finance Analytics - SQL

Problem Statement

AtliQ Hardware, a B2B manufacturer and distributor of computer peripherals, operated across multiple global markets but stored all operational data in Excel files — product sales, customer records, market data, and financial transactions. As business volumes scaled, Excel became the bottleneck: files crashed, reports took hours to refresh, and leadership had no reliable, real-time view of financial performance.

Project Overiew

This project addresses the problem in two phases:

  • Phase 1 Migrated all Excel data into a structured MySQL relational database.
  • Phase 2 Built a suite of automated finance analytics reports — replacing every manual Excel process with reusable, parameterised SQL artifacts.

Key Workstreams

  • Track profitability and revenue trends by market
  • Automate recurring business reporting
  • Built monthly product-level sales reports for Croma India
  • Developed customer-level gross sales tracking using stored procedures
  • Designed market segmentation logic (Gold vs Silver) based on sales thresholds
  • Created Top N analysis for markets, products, and customers by net sales
  • Generated regional performance breakdowns and contribution % analysis
  • Identified top 2 performing markets per region using ranking functions

Concepts Used

  • Stored Procedures
  • User Defined Functions (UDFs)
  • Views for modular reporting
  • Window Functions (DENSE_RANK, RANK, ROW_NUMBER, OVER())
  • Query Optimization Techniques

Impact

  • Reduced query runtime by ~78% (13s → 2.8s) by eliminating redundant UDF calls and introducing an optimized date dimension table.
  • Enabled faster and scalable financial reporting
  • Improved decision-making for market and product strategy
  • Built a reusable SQL framework for Top-N and segmentation analysis

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