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We enabled QSR Franchisee to significantly decrease time-to-action by 43%, leveraging the power of AWS Glue and Amazon QuickSight to transform and visualize their data

Challenge

INDUSTRY OVERVIEW

Our client is one of the largest restaurant operators in the Indian subcontinent operating over 800 restaurants

The architecture in place, while currently serving well, is not in line with the rapid growth in data volume. They want to eliminate manually generated MIS reports and design automated, interactive decision boards to make full utilization of the huge dataset they possess and make informed decisions by dedicated analysis.

CHALLENGE

They wanted eliminate manually generated MIS reports and design automated, interactive decision boards that reduce the time to truth and improve actionability

Gaps in the current system:

  • Reports are manually generated, and they take quite longer to generate
  • User role specific automated triggers to get rapid insights and stay ahead of any anomalies
  • No single source of truth as the same KPIs are being captured across multiple reports

They wanted to cut costs and time spent to manually process the data and reduce the time to truth for taking informed decisions

The customer sought Ganit's help to create automated, interactive decision boards to track the KPIs and understand the trends and patterns for improving the actionability

Why were we brought in?

Ganit has made a significant dent in various industries using data science and analysis. Ganit partners with clients to translate their data into a tangible, insightful plan of action that delivers on a measurable impact to the clients’ topline & bottom-line growth.

Our approach

Methodology

Ganit proposed the client to shift to AWS Quicksight for all their reporting needs to reduce the processing time and enhance the user experience by providing interactive dashboards

Data from all store POS systems is migrated every 15 minutes to the on prem central Headquarter SQL Server database.

The data from SQL server is migrated using batch jobs daily to AWS S3. The data is further cleaned and processed before loading to AWS Redshift.

There are various materialized data. The views are refreshed daily and connected to various QuickSight dashboards. The dashboards are used to calculate, track, and assess sales performance and other KPIs at monthly, weekly and daily levels.

An automated pipeline to deploy glue jobs & materialized views are developed in combination with AWS code commit & lambda functions.

Automated reports over email are configured on a weekly basis.

Features of the tool

  • Faster decision making; to cut overall costs and time spent.
  • Refined data is centrally located in the data warehouse.

A valuable difference

Impact

This approach not only helps the customer in decision making but at the same time helps them to cut costs and time spent to manually process the data (3 hours reduction in time taken for processing and loading of 1 TB of data) and provisioning for the capacity. With the proper table and query designs, the data is stored and processed conveniently without any hassle. Analyzing the data has become easy with all clean data centrally located in the data warehouse and visualized in AWS QuickSight.

Success stories

See the impact that we make on our
cross-industry client base.

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