Home » Built a Scalable, Personalized Digital Solution to Boost Customer Engagement for a Major Asset Management Company
Built a Scalable, Personalized Digital Solution to Boost Customer Engagement for a Major Asset Management Company
About the client
Largest Asset Management Firm
The growing volume and complexity of data necessitated an efficient data ingestion and processing solution.
Maintaining a scalable and high-performance data warehousing system.
Need for real-time or near-real-time data updates to ensure that insights are based on the latest information.
Developing and deploying machine learning models for personalization and recommendations
Creating actionable insights through visualizations to enable data-driven decision-making accessible to the business team.
The proposed solution involved a comprehensive approach to data management and analytics on AWS. Data ingestion and processing were seamlessly executed using AWS Glue, with Amazon Redshift serving as the data warehousing solution.
Lambda-based triggers were employed to automate and ensure the timely updates of data throughout the pipeline.
For personalization and recommendation, an ML model was developed and hosted on AWS, harnessing the power of Amazon SageMaker.
To derive actionable insights, visualizations, and interactive dashboards were created in Tableau, catering to the core business team's requirements.
This holistic architecture guaranteed a smooth data flow, advanced analytics capabilities, and data-driven decision-making, all while capitalizing on AWS's core strengths, including scalability, security, and user-friendly interfaces.
Created the data ingestion and data processing solution on AWS leveraging AWS Glue, Redshift, and lambda-based triggers
Created the ML model on AWS for personalization and recommendations
Visualizations on Tableau for core business team
Reduction in Data availability Time
Reduction in overall execution timelines
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