The use of HP Vertica as a big data core component to Vichara has allowed them to extend their easier to use financial modeling and tools, and then apply them to other industries such as insurance and healthcare.
To learn more about how advanced big data, cloud, and converged infrastructure implementations are expanding the impact and value of rapid and increasingly predictive analytics, BriefingsDirect sat down with Tim Meyer, Managing Director at Vichara Technologies at the recent HP Big Data 2014 Conference in Boston. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: Tell us how your organization evolved, and how big data has become such a large part of the marketplace for gaining insights into businesses.
Meyer: The company has its roots in analytics and risk modeling and for all sorts of instruments that are used on Wall Street for predicting prices and valuation of instruments. As the IT infrastructure grew from Excel to databases and eventually to very fast databases, such as Vertica, we realized that there were many problems that couldn't be solved before, and that required way too long a time to answer.
Gardner: How long have you been using Vertica? How did it become a part of your portfolio of services?
Meyer: We've been using Vertica for at least for two years now. It’s one of the early ones, and we recognized it as being one of the very fastest databases. We try to use as many of these components as possible. We really like Vertica for its capabilities.
Gardner: Tim, this whole notion of risk assessment is of interest to me. I think it's coming to bear on more industries. People are also interested in extending from knowing what has happened to being able to predict, and then better prescribe new efforts and new insights.
Tell me about predictive risk assessment. How do you go about that, and what should other companies understand about that?
Meyer: Risk assessment comes about from starting to look at how prices fluctuate and how interest rates move, and thus create changes in derivatives. What has happened most recently is that a lot of the banks and hedge funds have recognized this. Not only is [predictive risk assessment] a business imperative for them to have that half-percent hedge, but there are also compliance reasons for which they need to predict what their business is going to look like.
There are now more and more demands on stress testing, as well as demands from international banking regulations, such as Basel III, that require that businesses such as hedge funds and banks not just look behind, but ahead at how their business is going to look in a year. So this becomes really very important for a host of reasons even more than just how your business is doing.
Gardner: If I were a business and wanted to start taking advantage of what's now available through big-data analytics -- and at a more compelling price and higher performance than in the past -- what are some of the first steps?
Do I need to think about the type of data or the type of risk? How do you go about of recognizing that you can now get the technology to do this at an analytics level, but there is still the needed understanding of how to do it at the process and methodological level?
Meyer: We work very closely with our customers and try to separate algorithmic work from the development work. A lot of our customers have more than a few Caltech and MIT PhDs who do the algorithmic definitions. But all of them still need the engine, the machine with its scripting, and fast capability to build those queries right into the system as quickly as possible.
We usually work with these kinds of people, and it is a bit of a team-work effort. We find that that’s a way to figure out what is our value, and what is the value of our customer. Together, it has turned out to be very good teamwork.
Gardner: And you are a consultancy, as well as a services provider? Do you extend into any hosting or do you have a cloud approach? How do you manage the technology for the consulting and services you offer?
Meyer: We expand from the core products and tools into broader questions for people who want a proof of concept (POC) into this new technology. We build those on an ongoing basis. People, as well, want to look at options such as different performances of clouds. They do vary.
So we take on those kinds of consulting work as well, not to mention that sometimes it expands into back-office compliance and sometimes into billing issues. They all relate to the core business of managing portfolios, but yet they are linked.
Very often, we've done those kinds of projects and we see even more of these possibilities as we see compliance as a bigger issue, such as Dodd-Frank as well as Basel III, in the financial world. But they are really no different than many regulations coming on the healthcare side for paperwork management, for example.
Gardner: So that raises the question of the verticals that you expect first. Where is predictive risk assessment and the analytics requirements for that likely to appear first?
Meyer: One thing we have learned from our experience in financial modeling and tools is that there is always a need for people who are totally unskilled in SQL or other query languages to quickly get answers. Although many people have different takes on this, we think we've found some tools that are unique. And we think that these tools will apply to other industries, most particularly to healthcare.
These are big problems, but we think the way we think of it is to start small with a POC or really defining a very small problem and solving it and not trying to take a bite of the entire elephant, so to speak. We find that to be a much better approach to going into new segments and we'll be looking at both insurance and healthcare as two examples.
Gardner: Back to the technology front. Are there any developments in the technology arena that give you more confidence that you can take on any number of data types, information types, and scale and velocity types?
I'm thinking of looking at either cloud or converged infrastructure support of in-memory or columnar architectures. Is there a sense of confidence that no matter what you go to bite off in the market, you have the technology, and the technology partner, to back you up?
Meyer: We're finding that there is much more maturity in a lot of database technologies that are now coming out.
There is always something new on the horizon, but there are, as you said, columnar architectures and so on. These are already here, and we're constantly experimenting with them.
To your point about cloud infrastructure and where that is going, it's the same thing. We see ParAccel, Amazon, and data warehouses such as Redshift showing us the way where a lot of the technology is becoming very prepackaged. The value-add is to talk to the customer and speed up that process of integration.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
You may also be interested in:
- Large Russian bank, Otkritie Bank, turns to big data analysis to provide real-time financial insights
- Healthcare among most opportunistic use cases for boundaryless information flow improvement
- A practical guide to rapid IT Service Management as a foundation for overall business agility
- Journey to SAP quality — Home Trust builds center of excellence with HP ALM tools
- ITSM adoption forces a streamlined IT operations culture at Desjardins, paves the way to cloud
- Cloud services brokerages add needed elements of trust and oversight to complex cloud deals
- How Waste Management builds a powerful services continuum across IT operations, infrastructure, development, and processes
- GSN Games hits top prize using big data to uncover deep insights into gamer preferences
- Hybrid cloud models demand more infrastructure standardization, says global service provider Steria
- Service providers gain new levels of actionable customer intelligence from big data analytics