Case Study

Achieving a 78% Efficiency Boost by Automating Data Management for a Public Sector Road Transport Organization

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Government and PSU


Amazon S3, Amazon EC2, Amazon RDS, Amazon Redshift, AWS DMS, Amazon EventBridge


Streamlined data management solutions offering automation, cost reduction, seamless query execution, successful data transfers, and efficient scalability with AWS services

About the Client

The customer is a state-owned corporation that operates transport services across India, linking major metro towns in Andhra Pradesh, Karnataka, Maharashtra, Goa, Odisha, and Chhattisgarh, serving approximately 6 million passengers daily through three zones and multiple depots.



Data Management Efficiency Boost


Cost Reduction and Resource Optimization


Successful Data Transfer and Scalability

The Challenge

The customer faced challenges with managing large data volumes, facing scalability issues, and high storage costs. With over 650+GB of data on an FTP server, they aimed for seamless automation to enhance performance and scalability, aligning with their business needs.


  • Monthly migration begins by retrieving 650+GB of .zip files from on-premises FTP, transferring to Amazon EC2, and then to Amazon S3. .sql files are extracted for record insertion into Amazon RDS. 
  • Amazon EventBridge manages Amazon EC2 and Amazon RDS based on requirements. 
  • Approximately 28 tables migrate from Amazon RDS to Amazon Redshift Serverless using AWS Data Migration Service. 
  • Seamless integration between Amazon Redshift and AWS DMS ensures uninterrupted data transfer and synchronization. 
  • AWS DMS facilitates schema conversion, data replication, and synchronization, making Amazon Redshift a strategic choice. 
  • Amazon Redshift executes transformation queries, including aggregation and bunching, and implements stored procedures for efficiency. 
  • Transformation queries are scheduled on the 1st day monthly, minimizing manual intervention. 
  • PowerBI creates intuitive visualization dashboards for reporting. 

The Results

Achieved a 78% increase in data management efficiency, reduced operational costs by 35%-38%, seamlessly executed transformation queries, transferred over 650GB of data without loss, and effectively managed growing data volumes with scalable AWS services.

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