DL Billing Bloomberg
The Challenge
This tool has made it possible to identify and classify the use of Bloomberg information by department. Certain uncontrolled areas of unnecessary queries were identified and costs were optimized, reduced, and allocated. The automatic generation of reports and comparative graphs with monthly historical data led to a rethinking of the market data query strategy.
The Strategy
The ARENA Financial Tech team designs and creates an ad hoc tool that allows large data files to be ingested for matching, sorting and allocation using lightweight processes. To achieve this, we work in the JAVA environment with Spring Boot and Spring Batch, using an in-memory database optimised for reconciliation. Once the ingestion process is complete, the data must be extracted.
The Results
This tool has made it possible to identify and classify the use of Bloomberg information by department. Certain uncontrolled areas of unnecessary queries were identified and costs were optimised, reduced and allocated. The automatic generation of reports and comparative graphs with monthly historical data led to a rethinking of the market data query strategy.
Projetc FAQs
What problem does this Bloomberg DL Billing project address?
The project arose following changes to Bloomberg’s billing system that resulted in a loss of visibility into usage and billing by division and department, creating a need for better traceability and control.
What does the tool developed by ARENA Financial Tech do?
The solution enables the ingestion of large data files, which are then processed for matching, sorting, and assignment, facilitating reconciliation and the allocation of costs based on the source of the queries.
What technologies were used in developing the solution?
The application was developed in a Java environment using Spring Boot and Spring Batch, along with an in-memory database optimized for reconciliation processes.
