Case Studies | Cricket-Analysis

Cricket Analysis

We built a cricket analysis platform that enables users to upload, process, and analyze cricket match data efficiently. The system streamlines data uploads, automates column mapping, links related datasets, and generates dynamic reports. This solution empowered the client to transform raw cricket data into structured, reusable insights with improved speed and scalability.

Project : Web Application (Admin & Data Analysts)

Industry : Sports

Problems & Solutions

Problems

Solutions

Upload Module

Column Mapping

Problems Users needed to map uploaded sheet columns to database keys, which was time-consuming.

SolutionsImplemented dropdown-based mapping for tables & keys and stored reusable mappings in a cache table.

Repetitive Mapping

ProblemsUsers frequently uploaded sheets with the same structure, forcing repeated manual mapping.

SolutionsEnabled saving mapping configurations in the database so they can be automatically reused.

Handling Related Sheets

ProblemsMatch info sheets and scoreboard sheets required manual linking.

SolutionsIntegrated Cricsheet’s unique match ID to automatically link scoreboard and match info records.

Reports Module

Static Report Generation

ProblemsReports were hardcoded, making it difficult to scale or add new report types.

SolutionsDesigned a dynamic report system where queries/functions are stored in the database, enabling scalable and flexible report creation.

Report Speed Optimization

ProblemsReports were slow when handling large datasets.

SolutionsImplemented a performance strategy by fetching data in a single query, computing in JavaScript, caching results in Redis, and applying horizontal scaling for better performance.

Technologies Used

Frontend

Next.js

Backend

NestJS

Cloud & Infrastructure

OpenAI

Database

MongoDB

Project Duration

Month 1

Requirement gathering and Upload Module development.

Month 2

Reports Module development and data optimization.

Month 3

AI integration, performance tuning, and deployment.

Results Achieved

Simplified data upload and mapping workflows.

Automated repetitive mapping tasks with saved configurations.

Achieved seamless linking of related cricket datasets.

Delivered dynamic, scalable reports without hardcoding.

Improved report generation speed with caching and optimized queries.

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