Client

Investment bank

Sector

Financial industry

Methodology

SCRUM

Competencies

Financial industry

Technologies

Java, Angular, TypeScript, Hbase, Coherence, programming languages developed for the project

Business need:

The client required a platform where a large amount of data would be processed with high frequency of updates.
Data growth regarding financial transactions is several TB per day and based on this data calculations need to be run daily in real time or after closing the day.
There is another team – Quant Stats - responsible for this type of calculation. Therefore, due to dynamic nature of financial markets, all calculations must be repeatable at any given time.

What have we done?

The project is co-created with the client on the basis of one global team, in which individual regions are responsible for different components, and includes:
• bitemporal object-oriented data base (prepared both by experts in Poland and at the client's site);
• programming languages for creating data models (prepared both by experts in Poland and at the client's site);
• collection of microservices and libraries for data upload (prepared both by experts in Poland and at the client's site);
• collection of microservices for data processing (prepared both by experts in Poland and at the client's site);
• platform for processing calculations (prepared at the client's site).
The solution architecture is designed by:
• bitemporal solution BigData (Hbase plus Coherence);
• data uploading system including ETL library which enables data uploads from diverse formats and
supports majority of standard network protocols without necessity to write a code;
• system layer processing those data and coordinating Quant Stats team calculations;
• collection of DevOps tools to manage the whole platform;
• collection of web user interfaces.

The solution architecture is designed by:

• Bitemporal solution BigData (Hbase plus Coherence);
• Data uploading system including ETL library which enables data uploads from diverse formats and
supports majority of standard network protocols without necessity to write a code;
• System layer processing those data and coordinating Quant Stats team calculations;
• collection of DevOps tools to manage the whole platform;
• collection of web user interfaces.