250TB+ data processed for faster customer analytics & building effective data infrastructure
Processed huge volumes of customer and POS data, generating insights within seconds through scalable and highly effective data management and data infrastructure
Business Challenges
The client is among the world’s largest retailers with over 11,000 stores and more than 245 million customers visiting the stores on a weekly basis. The existing process of generating reports was extremely manual-intensive and took a few hours to generate. As a result, data was updated only once in 30-60 days limiting them to get the maximum value out of the campaign insight. They required a real-time unified customer analytics platform to generate customer insights and highly effective data infrastructure.
Sigmoid’s Solution
We architected a Hadoop-based solution using Apache Spark for ad-hoc analysis on customer data. We also enabled slice and dice’ on granular data that provided access to granular customer information such as weekly trends, penetration in terms of customer reach, etc.
Business Impact
We processed over 250TB of the customer and POS data to enable granular data access for enhanced customer analytics. Our approach helped replace the manual process of generating reports resulting in 60% faster reporting and saving more than 10,000 man-hours.
