Revolutionizing Investment Decision-Making: Cloud-Agnostic Platform for a Trading Startup

Location

USA

Industry

Client

The client is a dynamic startup in the next-gen investment banking space offering investment services, such as research, advice, and execution for investment managers and other financial institutions.

Highlights

DataArt has developed a modern data analytics and technology platform for the client, empowering a team of quants, data scientists, and financial analysts to adopt data-driven investing practices. This platform facilitates the development, execution, and evolution of models for pricing, risk assessment, investment strategies, trading algorithms, scenario analysis, portfolio analytics, and market surveillance, all supported by cloud-based data solutions.

The key features of the platform include:

Automatic management of data lake and multiple data pipelines through a workflow engine, enabling seamless data-driven investing.
Provision of batch and real-time data processing engines that offer tools (BI, reporting, ad-hoc querying, notebooks), and APIs for accessing data and analytics for a wide range of user workloads.
Deployment in AWS with a cloud-agnostic approach and a microservices architecture.
Use of Python, Scala, Spark, and AWS Athena for data workloads.
Processing of over 30 sources of market, fundamental, and alternative financial data, amounting to more than 2TB, leveraging cloud-based data solutions to deliver fast and reliable insights.

Client Benefits

The platform is a core part of the client’s business as it improves the investment decision-making process through data-driven investing.
The implemented solution made processing and analyzing data fast and error-proof, aligning perfectly with cloud-based data solutions standards.
Due to the platform’s cloud-agnostic nature, the client can easily license its technology to institutional investors, asset managers, and other buy-side firms, opening up additional business growth opportunities powered by cloud-based data solutions.

Technologies

Python

Scala

Kuberenetes

Apache Airflow

Flask

Jupiter Notebook

Kafka

Spark

AWS

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