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Datawatch Corporation: Datawatch Monarch for IBM Watson Analytics and IBM Cognos Analytics Now Available

Everyday business users now empowered with self-service data preparation
capabilities that drive more informed, strategic business decisions

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outdated information, due to data retrieval challenges and time-intensive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

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:

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

Safe Harbor Statement under the Private Securities Litigation Reform Act of
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.

© 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.
Media Contact:

Amanda Beaupre
Marketing Communications Manager, Datawatch Corporation
Twitter: @datawatch


This announcement is distributed by NASDAQ OMX Corporate Solutions on behalf of NASDAQ OMX Corporate Solutions clients.
The issuer of this announcement warrants that they are solely responsible for the content, accuracy and originality of the information contained therein.
Source: Datawatch Corporation via Globenewswire


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