The client lacked access to over 100 essential Business Key Performance Indicators (KPIs), hindering effective business management and customer management. Also, the existing solution did not accommodate future product launches, integrations, and expansions. This posed challenges for scalability and adaptability.
We delivered a solution that leveraged AWS cloud services and serverless architectures for flexibility, scalability, and cost-effectiveness in operations. The data platform incorporates a data lake and star schema-based storage for efficient storage and retrieval of analytics data, ensuring optimal performance and accessibility. ELT (Extract, Load, Transform) processes are built on Sprinkle, a platform built on the Spark framework, facilitating efficient data transformation and processing. AWS Redshift is employed as the data warehouse solution, providing robust storage and querying capabilities for structured data, enhancing data analysis and decision-making capabilities.
AWS Glue for ETL processing
AWS Redshift for cloud data warehouse
AWS S3 for object data storage
Python for custom connectors
The solution made possible data driven business insights that helped the client in better decision making on new products, and extending the reach of existing products and services.