BEDFORD, Mass., May 10, 2016 (GLOBE NEWSWIRE) -- Datawatch Corporation (NASDAQ-CM: DWCH) today announced the immediate availability of Datawatch Monarch for IBM Watson Analytics and IBM Cognos Analytics. Earlier this year, Datawatch revealed that IBM (NYSE: IBM) would resell Datawatch Monarch to deliver better and faster data access and self-service data preparation (prep) to its users. Beginning today, those users can leverage Monarch to prep less, analyze more and harness the power of IBM’s cognitive computing capabilities across the widest variety of data sources.
Data that provides the most analytical value has traditionally been locked away in previously inaccessible multi-structured and unstructured documents, such as text reports, web pages, PDFs, JSON and log files. And, in many instances, an organization’s source data is diverse and rarely presents itself in an analysis-ready format. As a result, hours are spent on manual data retrieval and prep processes.
The Datawatch Monarch self-service data prep solution enables data analysts and everyday business users to rapidly access, manipulate and blend data from virtually any source. Data can then be prepared for analysis in Watson Analytics and Cognos Analytics in a fraction of the time that it takes using spreadsheets and other manually-intensive measures.
“The majority of strategic business decisions are made on incomplete or outdated information, due to data retrieval challenges and time-intensive manual prep processes,” said Michael Morrison, president and CEO of Datawatch. “This is an unfortunate reality given the impact these decisions can have on a company’s bottom line and growth potential. Monarch enables Watson Analytics and Cognos Analytics users to obtain not only the right information, but all of the information, required to obtain a holistic view of the business, and then easily and rapidly prepare it for analysis. Rather than spend hours on mundane prep work, users can now devote their time to performing analysis that accelerates decision making and drives business value.”
IBM Vision
Dan Potter, Datawatch’s chief marketing officer, is scheduled to present on new advances in self-service data prep at the upcoming IBM Vision conference in Orlando, Florida. Potter will discuss how self-service data prep enables users, especially those in financial and operational performance management, to leverage a wider variety of data, and reap faster and more accurate results. He’ll also demonstrate how an optimized data file can be prepared for direct import into Watson Analytics and Cognos Analytics. Potter’s session will take place on Wednesday, May 11, at 11 a.m. ET.
To learn more about Datawatch Monarch for Watson Analytics and Cognos Analytics, go to: http://www.datawatch.com/ibm-analytics.
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.
Safe Harbor Statement under the Private Securities Litigation Reform Act of 1995
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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