Wednesday Jul 13, 2011

"Large scale data management" for Financial Services

The problem of managing large amounts of data - structured data for this writeup - is pervasive in the financial industry. Compliance, Risk, Analytics, Pricing etc. all require ingesting, cleansing, transforming, standardizing, aggregating, persisting, analyzing and reporting on very large quantities of data. Given Oracle's pedigree in data management, I don't think it would be a surprise to you that we have a large set of technologies that help our FSI customers with their data management issues. We are also taking these technologies to our partners and helping them achieve enterprise class scale and reliability for their applications using this "large scale data management" platform.

The following diagram shows the relevant technologies that collectively we call the LSDM platform.

The baseline is Exadata or large SPARC systems. Data movement technologies, GoldenGate and ODI are the layer above - the combination allowing users to move data from a database instance to another instance in near realtime (change data capture only) and manipulating it at the destination. The destination instance is 11g, and the Spatial option brings in Semantics into the equation. Semantic data stores are starting to become popular in the FSI, since modeling of complex and continuously morphing relationships is easier using semantics than relational databases. For an industry that builds products that are so intricate that most personnel - and machines - have no clue about the component parts of these products, semantics will likely be mandated by the regulators.

Above the database are the in-memory data technologies that can be used in a variety of ways – Coherence as the in-memory data grid, and TimesTen as the in-memory database. These technologies are essentially performance related technologies. Think of Coherence as a large data cache where the data is dynamically provisioned across memory resources of various servers, and compute can be shipped to these servers – moving the compute to the data which is typically faster than the other way around. TimesTen is a in-memory SQL database, which can be linked with the compute making the two be a part of the same address space, again accelerating performance.

And the BI layer sits above all these technologies, helping with analytics and reporting.

We are positioning this stack with our customers and our ISV partners, in the reference data and risk space. Both these areas need large volumes of data to be processed, and the ISVs that we have spoken with are excited about working with us.

 

Friday Jun 17, 2011

Technology focussed solutions for Financial Services

Just finished a short trip to London, where I presented our 3 new technology solutions for Financial Services to the Oracle Client Advisors for the top accounts in EMEA. The solutions were well received by all, with opportunities for all 3 in all the top accounts.

The solutions that we are focused on this FY are

- Large Scale Data Management platform

- Extreme Java platform

- Banking Modernization platform, which includes Payments Consolidation (Wholesale and Retail), Core Banking Modernization and Mainframe Offload.

My team's responsibility is to build the resilient platform that our financial customers can run their applications on. If they chose Oracle's applications such as Flexcube or Reveleus, we have done the hard work to tightly integrate these applications with our LSDM and BM platforms. If however a customer decides to run a competitive application, they should rest assured that we have done the best possible integration work with those applications too. And in the case of Capital Markets where Oracle does not have trading or risk assets, our LSDM and EJP solutions work with our partner applications such as GoldenSource, PolarLake, Calypso to name a few.

 I will detail these solutions in subsequent posts.

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