A couple years ago, Bloomberg executives began to think about how to reshape its ubiquitous terminal for a financial-services industry that's becoming increasingly more adept at data science and coding.
While the data giant's long-time clients are mostly interested in using the terminal to get data, check the news, and chat with colleagues or peers, a new type of user with more mature needs was starting to emerge that Bloomberg was eager to attract.
Quants, math whizzes who have programmed their way to the top of hedge funds and banks, wanted to manipulate that same information, building models and coding using an ever-growing amount of computing power.
And while Bloomberg built out tools on the terminal to meet the needs of its quant clients — and still offers them to terminal users — it quickly realized more advanced features were better suited to run on the cloud.
"The concept was how do you reshape the terminal so that quants can access all of the great data and analytics that exist in our platform already. Once we did that, we quickly realized this product is really appropriate in an enterprise setting off the desktop," said Bloomberg's global head of enterprise data Tony McManus in an interview with Insider.
"We should really run this in the cloud. We should make it available to all user types. We should open it up so that customers can connect their own databases and data sources to it. And that is not a desktop workflow. That's an enterprise workflow."
The result was BQuant Enterprise: a new data analytics tool intended to meet the advanced needs of quantitative users while also making data science more accessible to non-quants or asset managers that have yet to build up a substantial data-science team.
BQuant Enterprise connects Bloomberg's datasets, both traditional and alternative offerings, to a customer's internal data in a Python-based code environment, McManus said. Application programming interfaces (APIs) allow a quant fund to plug in Bloomberg's historical data or its portfolio optimizer into the fund's own system via BQuant Enterprise.
The goal is to allow teams to quickly share and adjust data and models across their organization while leveraging the power of the public cloud. BQuant Enterprise is compatible with Amazon Web Services and Microsoft Azure, with plans to include Google Cloud Platform as well.
Data providers go to where information flows, and recently that's been the public cloud, as more financial institutions incorporate the tech into their data strategies.
Nasdaq is upgrading its data business by making more than 250 data sets accessible in real-time via the public cloud. Snowflake launched its Wall Street-focused cloud to help clients knit together alternative and third-party data with the scale of cloud computing.
The launch of BQuant Enterprise also highlights that the data giant's terminal, which turns 40 this year, can't always meet the advanced needs of its most tech-forward clients, which have embraced the cloud.
BQuant Enterprise includes automated workflows that can streamline parts of the modelling like initial data exploration, back-testing, optimization, and visualization. Doing so means that model results are always up-to-date with the most recent data available.
Early adopters include the $49 billion asset manager Thornburg Investment Management, which began using it earlier this year, McManus said. BQuant Enterprise replaces a web application the firm had built to ingest and share data, according to Igor Kuznetsov, a Thornburg portfolio analytics manager.
"My team could immediately access a wide range of normalized data; spend less time manipulating it; apply additional back-testing capabilities; and generate more ideas faster than before," Kuznetsov said in a release announcing the tool.
Bloomberg is actively working to onboard more customers to the new tool, McManus said, declining to disclose specifics.
Cloud over terminal
Many of the top buy-side firms have already spent considerable resources building their own data-analytics teams and infrastructure. For instance, Two Sigma is planning to hire hundreds of engineers to work on its public-cloud projects.
BQuant is still offered on the terminal, but the Enterprise version includes advanced capabilities that can only be realized with the computing power and storage capacity that the cloud offers, McManus said. Plus, many buy-side firms have already migrated at least part of their data analytics and research efforts to the tech, he added.
"You want to work as part of a community of data scientists. You want to build out analytics and applications, and then distribute those beyond that environment," he said, talking about the new wave of Bloomberg clients who are being targeted with BQuant Enterprise.
"The one thing I can tell you is that almost every customer of every type that we talk to these days, even firms that you wouldn't have thought of in the past as being particularly quantitative in nature, are moving in this direction," McManus said.
