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By integrating widely-distributed legacy systems and implementing a cutting-edge data lake strategy, we enhanced operational visibility and real-time analytics for our client. This approach solved critical data challenges, leading to a streamlined, accurate, and user-friendly operational environment for both agents and members.

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Business Issue

\n

The client’s huge data sets residing in widely-distributed legacy systems resulted in a lack of system integration that would help improve and provide visibility of operations and real-time analytics. Other challenges included a lack of a customer master that was responsive and could be accessed across regions, module systems that needed to be accessed for proper data retrieval, and multiple touchpoints, which resulted in a higher probability of data corruption raising concerns regarding data reliability.

\n

The client needed to structure the ad-hoc IT systems which were error-prone, labor-intensive, and expensive to maintain.

\n

 

\n

 

\n

Solution

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We developed a pipeline with change data capture and distributed even streaming and no-SQL database components. We also created real-time data flow between different components with data validation and monitoring to ensure data reliability. We used the right tools for data aggregation to get faster query tools.

\n

Most tools were built on open source to save on infrastructure costs. We combined Dash and Plotly to create a real-time, interactive visualization of data, quick turnaround times, and streamlined disparate processes into agile, consistent, accurate, and user-friendly operations.

\n

 

\n

 

\n

Outcomes 

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The solution was rolled out across six Southeast Asian Countries and helped migrate 10 million policies. The customer master (Data Lake) maintains all cumulative data for customers. Applications use this data for operations reporting and analytics.

\n

Business teams gained valuable insights into the pipeline status of policies. Reporting improved, and Ad-hoc MIS reports could be created on demand. The new solution provided a single source of truth to Data scientists, MIS teams, business teams, and Points of Sale with the right and efficient APIs. Real-time alerts on data anomalies accurately monitor data quality. This reduced the error rate in the database and removed inefficiencies in the system that involved manual, laborious, one-off, inaccurate departmental efforts.

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