Students Used Datawatch Monarch and IBM Watson Analytics Software Tools to Blend Data from Disparate Sources and Perform Statistical Analysis
BEDFORD, Mass. – October 26, 2016 – 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 firstname.lastname@example.org.
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: datawatch.imarc.io.
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Any 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.
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Marketing Communications Manager, Datawatch Corporation
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