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 CorporationDatawatch
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.
Safe Harbor Statement under the Private Securities
Litigation Reform Act of 1995Any statements contained in
this press release that do not describe historical facts may
constitute forward-looking statements as that term is defined in
the Private Securities Litigation Reform Act of 1995. Any such
statements contained herein, including but not limited to those
relating to product performance and viability, are based on current
expectations, but are subject to a number of risks and
uncertainties that may cause actual results to differ materially
from expectations. The factors that could cause actual future
results to differ materially from current expectations include the
following: rapid technological change; Datawatch’s dependence on
the introduction of new products and product enhancements and
possible delays in those introductions; acceptance of new products
by the market, competition in the software industry generally, and
in the markets for next generation analytics in particular; and
Datawatch’s dependence on its principal products, proprietary
software technology and software licensed from third parties.
Further information on factors that could cause actual results to
differ from those anticipated is detailed in various
publicly-available documents, which include, but are not limited
to, filings made by Datawatch from time to time with the Securities
and Exchange Commission, including but not limited to, those
appearing in the Company’s Annual Report on Form 10-K for the year
ended September 30, 2015. Any forward-looking statements should be
considered in light of those factors.
© 2016 Datawatch Corporation. Datawatch and the Datawatch logo
are trademarks or registered trademarks of Datawatch Corporation in
the United States and/or other countries. All other names are
trademarks or registered trademarks of their respective
companies.
Source: Datawatch
Media Contact:
Amanda Beaupre
Marketing Communications Manager, Datawatch Corporation
amanda_beaupre@datawatch.com
978-275-8387
Twitter: @datawatch
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