Data Analysis Using Amazon Redshift: Financial Technology

About the client

A global leader in PCI technology & transaction processing, offering business value through electronic payments, financial transaction processing solutions & services. A payment systems leader who provides a well-established portfolio of technology solutions, state-of-the-art infrastructure and has over 24 years of experience in the payments domain.


Client wanted to provide value addition by providing analytics on transactional data like success/failure rates, types of cards used etc. Their existing hardware wasn’t “elastically expanding” or sufficient to support the business. Any on-premise Data Warehouse solution will also incur huge CAPEX and the Client were well past their budget deadlines to go for a CAPEX approval. Moreover, the Client’s IT team was also not technically equipped at that stage to handle this project.


Cloud Kinetics recommended to use Amazon Redshift with AWS EMR and Tableau for the Data Warehouse, ETL Processing and BI Reporting respectively. Data was processed at a faster rate than how it would have happened on-premise. Transactional data to the tune of 8 GB was masked and moved to S3; custom-made Pig scripts would ETL the data; data moved to Amazon Redshift and BI reports were created on Tableau. All costs were defined properly and were under total control. The environment was designed to be highly available and to scale on demand. Dev and UAT environments were only used on need. Backup for all production data was setup on a daily basis.

  • Foundation to support future business growth was laid
  • R and R studio used for Advance Analytics processing
  • Costs are definitive and controllable
  • Options for High Availability, scalability and more critically, on-demand availability of
  • resources are a major win for customer adopting the cloud
  • Simplicity & transparency of cloud IT estate/costs facilitated for IT team

Success Metrics

  • Faster processing of huge volume of data (4x faster processing than what it would have taken in an on-premise setup)
  • AWS infra setup with High availability & Scalability
  • Robust reporting coupled with effective costs by using Tableau
  • Easy Backup and Recovery
  • Development & QA environments hosted with controllable costs (No CAPEX and only optimized OPEX)
Tags: Amazon Web Services (AWS) Banking & FSI Data & Analytics Data Engineering Data Migration Data Modernization