A major CPG client was dependent on data downloads from various vendor partners, multiple Excel files, and a Microsoft SQL Server instance to power their dashboards. This setup required substantial effort to manage and maintain, leading to challenges with insight delivery delays, user experience, scalability, and automation.
Since the client was already using a data warehouse on AWS, it made sense to centralize their data processing and reporting there. Leveraging AWS services provided advantages like seamless scalability, faster processing times, robust logging, and efficient error handling.
To design a solution that would provide the client with a dashboard featuring fully refreshed weekly data, incorporating both descriptive and predictive analytics. This would allow the client to focus on their business operations instead of worrying about data maintenance.
The process began with data ingestion from various sources, utilizing the client's existing data ingestion framework. Tredence designed and developed the Revenue Growth Management (RGM) warehouse within the Redshift cluster and created the data science pipeline and web application using AWS serverless architecture.
Operational Efficiency:
Significantly reduced overhead in data management, allowing the client to concentrate on core business operations.
Predictive analytics:
Leveraging the web application and ML models, the client is better positioned to achieve higher goals in a competitive market.
Dynamic ML Framework:
Delivered a fully dynamic and configurable, ready-to-use, end-to-end machine learning framework.
