Optimizing Data Pipelines for Retail
This project significantly improved data processing for a retail client, leading to faster insights and better decision-making.
Project Overview
This case study explores how we optimized data pipelines for a leading retail company, enhancing their data processing speed and accuracy.
Challenges
The client faced significant delays in data processing, which affected their decision-making capabilities. Our team identified bottlenecks in their existing architecture.
Solutions Implemented
We implemented a new ETL process using Apache Spark, which reduced processing time by 50%.
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