Transcript of a Briefings Direct podcast on how one consultancy is looking to expand its horizons for big-data analytics.

1. After Cutting its Big Data Teeth on Wall Street, Vichara
Technologies Grows the Market for Advanced Analytics
Transcript of a Briefings Direct podcast on how one consultancy is looking to expand its
horizons for big-data analytics.
Listen to the podcast. Find it on iTunes. Sponsor: HP
Dana Gardner: Hello, and welcome to the next edition of the HP Discover Podcast Series. I'm
Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this
ongoing sponsored discussion on IT innovation and how it’s making an impact
on people’s lives.
Once again, we're focusing on how companies are adapting to the new style of
IT to improve IT performance and deliver better user experiences, as well as
better business results.
This time, we're coming to you directly from the HP Big Data 2014 Conference
Gardner
in Boston. We're here the week of August 11 to learn directly from IT and business leaders alike
how big data, cloud, and converged infrastructure implementations are supporting their goals.
Our next innovation case study interview highlights how Vichara Technologies in Hoboken, New
Jersey is expanding its capabilities in big data from origins on Wall Street and in the financial
sector into other areas and demonstrating the growing marketplace for big-data analytics
services.
With that, please join me in welcoming our guest. We're here with Tim Meyer, the Managing
Director at Vichara Technologies. Welcome Tim.
Tim Meyer: Thank you, glad to be here Dana.
Gardner: First off, Tim, tell us how your organization evolved and how big
data has become such a big part of the marketplace in new areas, new verticals
and how they're demanding insights into their 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
Meyer
were many problems that couldn't be solved before and that required way too long a time to
answer.

2. Wall Street people measure time in seconds, not in hours. We've found that there's a great value
in answering a lot of business intelligence (BI) questions especially around valuations and risk
models, as well as portfolio management. These are very large portfolios and datasets that have
to be analyzed. We think that this is a great use of big-data analytics.
Gardner: How long have you been using Vertica? How long has that become a part of your
portfolio 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 fast databases. We try to use as many of these
components as possible. We really like Vertica for its capabilities.
Risk assessment
Gardner: Tim, this whole notion of risk assessment is of interest to me. I think it's now
coming to bear on more industries, and people are also interested in extending
from knowing what they've got to being able to predict, and then eventually
prescribe new efforts and new insights.
Tell me about risk assessment? How do you go about that, and what should
other companies understand about that if they wanted to start doing more with
themselves?
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 it. Not only is it 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 performance metric 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 analytic level, but there is still the
understanding of how to do it at the process at mythological level?
Meyer: Right. 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

3. 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 teamwork. 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 a 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?
Broader questions
Meyer: We do expand from the core products and tools into broader questions of 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.
Gardner: So that raises the question the verticals that you expect to be going to first. Where is
risk assessment and the analytics requirements for that first likely to appear?
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 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 w '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?

4. 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've got technology and the technology partner to back you up?
Meyer: Dana, that's a great point. We 'e finding that there is much more of a maturity in a lot of
database technologies that are coming.
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.
Gardner: Great. I'm afraid we will have to leave it there. We've been talking with Vichara
Technologies about how they have gathered some expertise in the financial sector and are now
looking to expand into such areas as insurance and healthcare. So a big thank you to our guest.
We're here with Tim Meyer, Managing Director at Vichara Technologies in Hoboken, New
Jersey. Thank you, Tim.
Meyer: Thank you, Dana.
Gardner: This is Dana Gardner, Principal Analyst at Interarbor Solutions. A big thank you also
to our audience for joining us in this special new style of IT discussion, coming to you directly
from the HP Big Data 2014 Conference in Boston. Thanks again for listening, and come back
next time.
Listen to the podcast. Find it on iTunes. Sponsor: HP
Transcript of a Briefings Direct podcast on how one consultancy is looking to expand its
horizons for big-data analytics. Copyright Interarbor Solutions, LLC, 2005-2014. All rights
reserved.
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