Personalized Recommendation Engine using Data Lake for a Leading American Telecom Operator
About the Client
The client is a major mobile network operator in the US, serving more than 5 million customers across states.
Business Requirement
- To create a single source of truth & feed 360-degree customer data to a Personalized Recommendation Engine which helps identify the right products for customers based on usage patterns & preferences
Our Solution
- Designed & created a Hadoop based Data Lake as a common source for all customer data
- Created Talend based pipelines to source data from EDW, local data marts, etc. at predefined frequencies
- Created a configurable batch engine to parameterize the running of the pipelines for processing of data
Process Flow
Business Outcomes
- Rapid turnaround time of less than 4 months
- Single platform for all customer data with up-to-date information and provisions to include additional structured & unstructured data
- Inherent scalability of the platform to handle data from few hundred Gigabytes to several Petabytes