About a-team Marketing Services

A-Team Insight Blogs

A-Team Webinar to Discuss Data Transformation in Quant Research and Trading

Subscribe to our newsletter

Quantitative workflows rely on sourcing, aggregating, normalising and managing data. This can be highly resource-intensive, leading to a situation where some financial institutions with quant shops are more focused on data management than on data science and modeling.

So how can the data ingestion, management, and pipeline processes of quant workflows be streamlined, allowing quants to concentrate on their primary responsibilities such as building models, testing them, exploring alternative data sources, accessing available data models and libraries, and ultimately generating alpha?

This will be the subject of A-Team Group’s upcoming webinar on 14th March 2023, ‘Transforming Data Experiences in Quantitative Research and Trading’, featuring James McGeehan, Industry Principal, Financial Services and Bryan Lenker, Industry Field CTO, Financial Services at Snowflake.

“The data wrangling challenge in data science is significant,” says McGeehan. “With the increasing volume, variety, velocity, and veracity of data, having the ability to process, test and run transactional and analytical workloads and to speed up time to value is crucial, particularly with the real-time data sets needed in the financial markets space. Being able to simplify infrastructure, break down data silos, and enable quick insights is becoming increasingly essential.”

The webinar will look at how leading firms are transforming their data architectures and leveraging native application frameworks to access more data, power quantitative models, uncover unique insights and ultimately add value to their end users and customers.

“One of the key challenges is accessing and utilising multiple sources of data,” says Lenker. “Legacy technology platforms are unable to manage this end-to-end. Thus, organisations need to adopt a technology stack that enables users to access, build models with, and share data efficiently. Instead of relying on multiple tools and channels, organisations should approach their enterprise data strategy as a holistic entity and consider how and where the data output will be shared, internally or externally.”

“Multiple taxonomies and physical data movement cause redundant copies, stale data, and incomplete analysis,” adds McGeehan. “Modern application frameworks that unify data intelligence without physical movement, bringing intelligence to data in a secure environment, are key to achieving faster investment research, reducing data management, promoting security and governance, and enabling quicker monetisation.”

Please join us for what we expect will be an informative and enlightening discussion.

Subscribe to our newsletter

Related content


Recorded Webinar: High-performance, real-time multi-stream data processing for trading analytics and risk management

Financial analytics platforms in Hedge Funds are often segmented between real-time and back-office analytics systems fed by slower batch processes. To support winning analytics, hedge funds and other trading firms need to bring together real-time streams with historical analytic data in a single high-performance data store to refresh reports and risk models in near-real-time. Listen...


A-Team Group’s Lorna Van Zyl Featured on FinTech Focus TV, Discussing TradingTech Summit London

In anticipation of this year’s TradingTech Summit London, we’re delighted that A-Team Group’s Head of Event Content, Lorna Van Zyl, was the star guest on the latest episode of FinTech Focus TV, talking with Toby Babb of Harrington Starr. In a wide-ranging interview, Lorna shares what goes on behind the scenes when putting the event...


Data Management Summit New York City

Now in its 12th year, the Data Management Summit (DMS) in New York brings together the North American, capital markets enterprise data management community, to explore the evolution of data strategy and how to leverage data to drive compliance and business insight.


Connecting to Today’s Fast Markets

At the same time, the growth of high frequency and event-driven trading techniques is spurring demand for direct feed services sourced from exchanges and other trading venues, including alternative trading systems and multilateral trading facilities. Handling these high-speed data feeds its presenting market data managers and their infrastructure teams with a challenge: how to manage...