MayStreet, the industry’s leading market data technology and content provider, announced the launch of the next generation of Analytics Workbench, the firm’s ready-to-use, cloud-based market data analytics environment. Through Analytics Workbench, data analysts can quickly and efficiently query the MayStreet Market Data Lake to drive mission-critical trading workflows without having to manage data capture, delivery or storage.
Key features of new Analytics Workbench include the ability to:
- Query and extract data using Python or R for analysis within Workbench or in any other location, whether in the cloud or on-premise
- Leverage pre-configured Jupyter notebooks to support out-of-the-box query capabilities
- Perform ad-hoc analyses or schedule batch jobs to support ongoing reporting requirements
- Instantly parallelize and scale ad-hoc or scheduled code across the cloud with integrated support for Dask clusters
- Upload internal order data or other third-party data to leverage in conjunction with MayStreet market data to support TCA, fill analysis and best execution reporting
- Query results provided in normalized or raw PCAP formats and create reports using powerful visualization tools
- Flexible deployment options, either fully managed within MayStreet’s cloud environment or integrated within a client’s cloud
- Achieve performance objectives with optimized cluster parallelization
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Commenting on the launch, Naftali Cohen, MayStreet’s Chief Revenue Officer, said: “The completely revamped Analytics Workbench realizes our goal of letting users bring their queries to our data, freeing them from the difficult and costly work of managing the data themselves. For the first time, our vast repository of ultra-high-quality global market data is accessible in a ready-to-use environment that leverages cloud economics. It’s also highly customizable, letting clients choose the level of performance they desire so that costs can be managed based on their needs. For capital markets data analysts, the new Analytics Workbench is a true gamechanger.”
Dave Thompson, Senior Vice President, Frontend Engineering, added: “In the process of redeveloping Analytics Workbench from the ground up, we identified several tools such as Dremio, Dask and Jupyter that could elevate its performance, functionality and scalability. By integrating these and other technologies, we have been able to create a truly modern data access and analytics tool built for the cloud. We’ve had many conversations with clients over the past 18 months about their hopes for a product like this, and we’re very pleased with the end result.”
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The new version of Analytics Workbench is currently being used by multiple clients, including a global investment bank, an exchange and a quantitative hedge fund. MayStreet expects additional clients to begin using the product over the coming weeks. Analytics Workbench was used by market structure researchers Robert Bartlett, Justin McCrary and Maureen O’Hara for their recent paper on the impact of odd lot quotes.
“MayStreet’s comprehensive, high-quality exchange data allowed us to document the vital importance of odd lot quotes in today’s equity markets, especially for higher-priced stocks,” said Bartlett, Faculty Director at the Berkeley Center for Law, Business and the Economy. “Without reliable access to the historical data feeds for all exchanges, such a study would simply not be possible given that these quotes are excluded from the SIP data. Additionally, leveraging MayStreet’s Analytics Workbench gave us the computational capacity we needed to process quickly the vast quantities of data.”
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