CASE STUDIES

AI enabled system to process millions of unstructured data for a retailer

SUMMARY

One of the retailer clients was having difficulty in processing a very large volume of data from different sales channels. Their hadoop based infrastructure was unable to implement the process successfully. The client wanted to have a single source of data and also to increase the processing speed while deploying the various algorithms to make effective models.

METHODOLOGY

• Shifting of Hadoop based infrastructure to Google Cloud Platform

• Using the GCP infrastructure to help the data scientists in a cost effective way

• Merging of various parameters with regard to customer

TAKE AWAYS

• Cost efficient and auto scalable infrastructure

• Managing a wide range of ML models

END RESULTS

• A huge volume of data being processed in a given time frame.

• Increase in the speed of processing.

• Cost reduction by more than 30%.