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Bloomberg Eases Data Access and Reduces Costs with Enterprise Access Point

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Bloomberg has responded to customer calls for easier access to data with Enterprise Access Point, an online platform that provides normalised reference, pricing, regulatory and historical datasets to Bloomberg data license holders. Following the launch of the platform last week, we caught up with Gerard Francis, global head of enterprise data at Bloomberg, to find out more about the service and its potential going forward.

He says: “Enterprise Access Point responds to customer challenges of understanding what data they have already licensed and what data would be useful to them, and normalising the data – we do that for them. The platform also makes data directly programmable for developers and data scientists.”

Francis describes Enterprise Access Point as a managed service and notes that it makes no changes to the company’s data license model. It uses open technology standards to encourage adoption, covers all data except real-time data, and is based on the Bloomberg cloud, allowing clients who are permissioned to pull data directly from the platform’s website. Francis comments: “For existing clients, data is easier to access and integration and normalisation costs are reduced, if not completely eliminated. For new clients, the platform makes data very accessible very quickly.” Qualifying cost reduction, he says the industry norm is that every dollar spent on data requires a further $5 to $7 dollars to make the data ready to consume. Enterprise Access Point reduces that cost.

By pre-preparing data, the platform allows users to browse quality data online, examine the metadata, trial sample datasets prior to acquisition, and immediately put them to use. If a user is not licensed to use particular data, the top 10 rows of the data can be accessed to give the user a feel for whether it could be useful and whether to subscribe for the data.

For business users, access to the data is provided by a RESTful API. Francis suggests use cases including improved risk management.

For developers and data scientists, data from Enterprise Access Point is available as CSV data frames and supports multiple technologies including Jupyter and Python Pandas. For professionals leveraging artificial intelligence (AI), the data is also available in a graph format. Web developers using the service can benefits from Bloomberg’s RESTful Hypermedia API, which allows URL consistent data to feed directly into an enterprise’s software components, including machine learning tools.

With historical datasets covering the past 10 years, Francis notes potential use of the platform by not only data scientists, but also quants and compliance teams working on Fundamental Review of the Trading Book (FRTB) regulation.

Matthew Rawlings, chief data officer in Bloomberg’s enterprise data department, says: “Having access to deep data history is critical for any investing or business governance strategy based on data science insights. By providing consistent data feeds along with history through API protocols, Enterprise Access Point allows scientists to apply data models with greater confidence and efficiency.”

Enterprise Access Point initially offers Bloomberg data, including some alternative datasets, but this is expected to change over time as more and different data is added to the platform.

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