Students Used Datawatch Monarch and IBM Watson Analytics Software
Tools to Blend Data from Disparate Sources and Perform Statistical
Analysis
BEDFORD, Mass., Oct. 26, 2016 (GLOBE
NEWSWIRE) -- Datawatch Corporation (NASDAQ-CM:DWCH) today
announced the results of the Datawatch and IBM Watson Analytics
Hackathon, which took place at the University of New Hampshire
(UNH) Peter T. Paul Entrepreneurship Center (ECenter) on
October 21 and 22. Utilizing the Datawatch Monarch data preparation
platform and IBM Watson Analytics software, a winning team of
students combined numerous, disparate data sources and performed
automated, predictive analysis to make a compelling case for how
Donald J. Trump can win the popular vote this presidential
election.
The Datawatch and IBM Watson
Analytics Hackathon was a 20-hour event that brought together
approximately 40 UNH students from all colleges and majors to
examine and analyze data sets related to demographics and the 2016
United States presidential election. Designed to introduce students
to the revolutionary analytics approach that is smart data
discovery, the hands-on workshop afforded participants the
opportunity to utilize innovative software and experience the power
of collaborative analysis.
"I don't believe any of the participants were
political science majors, but they had quite a bit of political
insight and were able to use the datasets in meaningful ways," said
Andy Smith, director of the UNH Survey Center. "Being a
political scientist myself, I was impressed. I commend the students
for their dedication to the competition and the high quality of
their presentations. The teams had a lot to accomplish in a short
time, with a steep learning curve and software they weren't
familiar with."
After receiving a 30-minute introduction
to Datawatch Monarch and a 120-minute demonstration of
Watson Analytics, 10 student teams were unleashed with several data
sets and the software tools at 4 p.m. ET on Friday, October 21.
They were required to submit PowerPoint presentations of their
analyses to the judges at the UNH ECenter by 10 a.m. ET Saturday,
October 22. Judges Andy Smith, Dan Potter, CMO of Datawatch, and
Laura Trouvais, academic program administrator of IBM, evaluated
the presentations based on six criteria, including: proficiency in
using each tool; creativity and logic in how the analysis was
conducted and insights were identified; the usefulness of those
insights; and the data visualizations, logic and flow of the
presentation.
Once the students formulated their hypotheses,
they used Datawatch Monarch to unlock and blend data from numerous
data sources and formats such as PDFs, CSV files, Excel and Access
databases, web content from several published sources and sentiment
data from social networks. The prepared data was then processed in
IBM Watson Analytics in the cloud, allowing the teams to create
data visualizations and dashboards in minutes.
"It was remarkable to see the depth of new
insights students were able to quickly gain by bringing together
disparate sources with Monarch and performing advanced analytics
with IBM Watson," commented Dan Potter. "The students didn't have
any proficiency in the blending or analytics tools just 24 hours
earlier. Their performance and the results of the competition are a
testament to how far this technology has come that people with no
previous experience with the software can immediately derive value
from their data."
Laura Trouvais added, "We were glad to participate
in the hackathon. We love going to this type of event because it's
so refreshing to see students engaged with and interested in the
products. The UNH students handled the challenge well, and got a
taste of real-world analytics with Watson Analytics and Datawatch
Monarch."
The winning team, comprised of undergraduate
students Brandon Allen, TJ Evarts, Max Miller and Sam Warach,
analyzed U.S. Census data and state polling information, as well as
data from the 2012 presidential election to determine the total
number of current voters for Donald Trump and Hillary Clinton.
Using IBM Watson, they generated a line graph of voter loyalty for
each candidate throughout the past 10 months, which revealed that
Trump's core voter base has remained more consistent than
Clinton's. The team determined that if voters cast their ballots
"today," Clinton would win the popular vote by only four percent;
however, if Clinton's voters, who have been historically quick to
change their opinion of the democratic candidate, move to a third
party, Trump can conceivably win the popular vote.
"I can speak for all of us when I say that we're
really excited to have been able to participate in this competition
- and of course to have won," said Sam Warach, Finance and
International Affairs student at UNH (Class of 2017). "We're all
very grateful for this opportunity."
In addition to enjoying the prestige of the
hackathon win, the winning team members took advantage of an
all-expenses paid trip to IBM's World of
Watson conference in Las Vegas this week to participate in an
IBM academic program and present their findings.
For more information about the Hackathon or to
obtain a copy of the winning team's presidential analysis, please
contact datawatch@teamlewis.com.
About Datawatch
Corporation
Datawatch Corporation (NASDAQ-CM:DWCH) enables ordinary users
to achieve extraordinary results with their data. Only
Datawatch can unlock data from the widest variety of sources and
prepare it for use in visualization and analytics tools, or for
other business processes. When real-time visibility into
rapidly changing data is critical, Datawatch also enables users to
analyze streaming data, even in the most demanding environments,
such as capital markets. Organizations of all sizes in more than
100 countries worldwide use Datawatch products, including 93 of the
Fortune 100. The company is headquartered in Bedford,
Massachusetts, with offices in New York, London, Frankfurt,
Stockholm, Singapore and Manila. To learn more about Datawatch
or download a free version of its enterprise software, please
visit: www.datawatch.com.
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the Private Securities Litigation Reform Act of
1995
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term is defined in the Private Securities Litigation Reform Act of
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limited to those relating to product performance and viability, are
based on current expectations, but are subject to a number of risks
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materially from expectations. The factors that could cause actual
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Source: Datawatch
Media Contact:
Amanda Beaupre
Marketing Communications Manager, Datawatch Corporation
amanda_beaupre@datawatch.com
978-275-8387
Twitter: @datawatch