MayStreet enhances Analytics Workbench on data lake
MayStreet’s Market Data Lake has recently introduced full-depth-of-book data for all US-listed options markets and added all major equities and futures markets in Asia-Pacific.
MayStreet has launched a cloud-based market data analytics environment, Analytics Workbench, where 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.
The market data technology and content provider said 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, but more clients will be added to the cloud over the coming weeks.
Latest in series of enhancements to MayStreet Market Data Lake
This is the latest in a series of enhancements to the MayStreet Market Data Lake, which now includes access through a new High-Performance Query (HPQ) API, the introduction of full-depth-of-book data for all US-listed options markets, and the round out of its global coverage with the addition of all major equities and futures markets in Asia-Pacific.
MayStreet’s new version of Analytics Workbench features 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.
Naftali Cohen, Chief Revenue Officer at MayStreet, 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.”
