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A leading food and grocery retailer in India with a significant presence across India that supplies plethora of products most of them falling under grocery and food retail segment was not convinced with the results they were getting from their existing report-serving architecture and wanted a much more robust, cost efficient and analysis friendly data storage solution with integrated pipelines to get quick and powerful insights from the data.

We made a visible and measurable impact to our client's business

100,000+ man hours saved per year

Challenge

Industry Overview

Initially they were using the conventional systems like RMS and LS Retail system but those didn’t prove to be efficient enough and the client was not getting any tangible results.

Problem Overview

The retailer was not convinced with the results they were getting from their existing report-serving architecture and wanted a much more robust, cost efficient and analysis friendly data storage solution with integrated pipelines to get quick and powerful insights from the data to facilitate decision making process.

Why were we brought in?

The company asked to create a measurable impact to our their business a major chunk of these solutions involving an AWS based architecture or services.

Our approach

Methodology

  • Ganit proposed the client to shift to AWS Redshift for their data warehousing needs with integrations to various other AWS services for smooth data ingestion, data analysis and dashboard creation to help facilitate the decision-making process for their management team.
  • For the data ingestion the data is unloaded into an S3 bucket from where it is processed using ETL and the processed data is shifted to Amazon Redshift.
  • To speed up the querying and data extraction process Redshift Spectrum is used which enable the client to directly query the data from Amazon S3, cutting down expense and time consumed.
  • Also, the Redshift is directly connected with various BI tools like quick sight and tableau for creating dashboards to measure different KPI’s which ultimately facilitates the client’s decision making. Also, the recurring reports are being automated using Apache Airflow and sent to clients within the specified interval.

A valuable difference

Impact

This approach not only helps the retail gaint in decision making but at the same time helps them to cut costs and time spent to manually process the data. With the proper table and query designs the data is stored and processed conveniently without any hassle.

To speed up the querying and data extraction process Redshift Spectrum is used which enable the client to directly query the data from Amazon S3, cutting down expense and time consumed.

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