Assisted a digital marketing company to optimize KPIs and increase...Read More
The client is a multi-national private banking and financial services company based out of India. With subsidiaries on a global platform, the client provides banking and financial products and services to retail and corporate customers.
The client wanted to build a secure and scalable No-SQL capable Data Mart to achieve low-latency API-based query response for its banking and financial applications.
We helped the client find the right tool to achieve business requirements with high availability,
scalability, reliability, and SLA. We modified and optimized ETL workflows and designed an ingestion mechanism for the Data Mart architecture. For analysis of performance, we selected two Market leaders, MapR-DB and Mongo DB, developed independent optimized APIs to connect to these environments and perform routine activities.
The solution helped the client select the best suitable tool, Mongo DB, for providing the least response time for API requests. Drawbacks as compared to MapR, i.e., slower bulk operations and ineffective batch processing, were handled by introducing multiple shards and replica environments with NVMe storage. The query performance was improved by 200% and low latency.
Aptus Data Labs used the following methodology approach to plan, develop, and execute the workflow and solve existing challenges. Aptus Data Labs:
|Big Data Platform||Testing & Automation||Monitoring|
MapR Hadoop, Mongo DB, Python, Java
Bash scripting, SQL, Postman, Mongoose