Built a Scalable, Personalized Digital Solution to Boost Customer Engagement for a Major Asset Management Company

About the client

Largest Asset Management Firm

Challenges

• 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.

Approach

• 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.

Solution

• 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