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First Derivatives and Pivotal Collaborate on Next-Generation Data Architecture

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First Derivatives (FD) is providing consulting services around technology from Pivotal with a view to helping customers build next-generation data architectures and applications for risk management, regulatory compliance, market surveillance and trading. FD will work initially to help clients install and commission Pivotal software and build out intelligent data lakes using semantic tagging, but expects the relationship to run deeper over time.

Pivotal was spun out of EMC and VMware last year to provide a data analysis platform-as-a-service (Paas) solution. It has since developed Pivotal One, a multi-cloud enterprise PaaS that includes a set of application and data services that run on top of Pivotal CF, an enterprise distribution version of the open source Cloud Foundry. FD intends to help clients accelerate adoption of Pivotal One services such as Pivotal HD for Hadoop implementation, Pivotal Data Dispatch for data retrieval and analysis, Pivotal RabbitMQ for message delivery and Pivotal MySQL for rapid application development and testing.

Gerry Buggy, executive at FD, suggests the emergence of Big Data and its characteristics of volume, velocity and variety means financial services firms are moving away from traditional data repositories and towards enterprise data architectures that are based on data relationships, curation, ontology and meta data repositories, and can support real time access to all types of data from all types of sources.

In terms of FD’s relationship with Pivotal, he explains: “The collaboration enables us to overlay our domain expertise on top of Pivotal’s future state financial services architecture. Services for risk, trading and regulation require unobstructed access to intelligent data. Customers are seeking best practice installation, alongside services such as semantic data tagging of items spanning real time to off line and structured to unstructured data.”

Russell Acton, vice president of EMEA at Pivotal, adds: “There is no substitute for data insight and understanding, and no industry knows this better than the financial services sector. Our collaboration with First Derivatives will help firms take advantage of Pivotal technologies and allow them to store data at scale, analyse anything and build the right application for their needs. And they will be able to do this in ways that are much more agile and value driven than in the past.”

FD is well positioned to help clients with the data elements of Pivotal deployments as its consulting practice covers areas such as time series, risk and compliance. It also has a heritage in the velocity aspect of Big Data as a result of its partnership with Kx Systems, a provider of high volume, high performance databases, and expertise in data mapping and transaction processing. The company will develop XML models to define data that will be processed by the Pivotal systems and can support customers tagging data or supply semantically tagged data models covering, perhaps, reference data, instrument data or client data needed to comply with regulations such as Basel III, Dodd Frank, Know Your Customer and Anti-Money Laundering.

Large investment banks and other large buy-side organisations are the early adopters of next generation data architectures for Big Data, partly because existing data management solutions are hitting capacity, and partly because they are looking for cost savings that can be achieved by using open source technologies.

Buggy says some firms are working on the type of open data architecture proposed by Pivotal and others have it on their radar. Risk and compliance will be the first data segments to move over, with work still being done to discover how trade processing can best benefit from such data architectures.

While projects are taking shape, Buggy does not expect firms to replace entire data management systems, but instead begin to build out risk, compliance and surveillance applications and analytics that traverse datasets and use data in a way that was not previously possible. He comments: “Data analysis using data that is semantically tagged will look like nothing we have seen before.”

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