Datawatch Brings Powerful Self-Service Data Preparation Capabilities to IBM Watson Analytics and IBM Cognos Analytics Users
BEDFORD, Mass., March 14, 2016 -- Datawatch Corporation (NASDAQ-CM: DWCH) today announced it has teamed with IBM (NYSE: IBM) to deliver better and faster data access and self-service data preparation to IBM Watson Analytics and IBM Cognos Analytics users. As part of this agreement, IBM will resell Datawatch Monarch, Datawatch’s market-leading self-service data preparation solution, which enables business analysts to rapidly access, manipulate and blend data from the widest variety of sources.
Self-service data preparation is one of the key components in an effective analytics strategy; however in many instances an organization’s source data is diverse and rarely presents itself in a form that is accessible or in the format needed to perform analytics. Data sources come in a wide range of report formats, which often require IT intervention to make it usable to the average line of business user or citizen analyst. In fact, business analysts and data scientists typically spend up to 80 percent1 of their time manually preparing data, and it’s estimated that only 12 percent2 of enterprise data is used today to make decisions.
With Datawatch Monarch, IBM Watson Analytics and Cognos Analytics users can now rapidly prepare data from virtually any information source, from traditional databases to multi-structured documents, such as PDF and text reports, Web pages, JSON and log files that had previously been locked away. Data can now be prepared for analysis in a fraction of the time that it takes using spreadsheets and other manually-intensive measures.
“Many organizations still do not have access to the underlying data needed for critical business insights and as a result are spending entirely too much time preparing data and not enough time analyzing,” said Marc Altshuller, Vice President, Watson Analytics and Business Intelligence, IBM Analytics. “The ability to simply send data accessed and prepared in Datawatch directly to Watson Analytics and Cognos Analytics will enable businesses to quickly select any data source and automatically convert it into structured data for analysis. This will not only expedite time to insight, but it increases the likelihood of uncovering new insights that have the potential to transform the business.”
Additional features of Datawatch Monarch for Watson Analytics and Cognos Analytics include:
The Fauquier Bank, established in 1902, is an independent, locally-owned community bank offering a full range of financial services for commercial and retail customers including internet banking, insurance, wealth management and financial planning based in Virginia.
“Datawatch has increased the use of information throughout the organization. Before this, it was inconceivable to bring data from different areas into one data set that could be used for security, marketing, audits and other business line decisions that would directly impact the bottom line,” said Janet Grimsley, Vice President, Decision Support. “The new relationship with IBM Watson Analytics extends the value by delivering powerful predictive analytics capabilities using simple natural language queries.”
Southeastern Med is an acute healthcare center serving some 4,000 inpatients and 100,000 outpatients. Similarly, they use Datawatch to access and prepare data from previously inaccessible sources like PDF reports to provide a more comprehensive understanding of their business and conform to regulatory requirements
“We think the combination of Datawatch and IBM Watson Analytics is very well suited for self-service analytics,” said Clark Carpenter, infrastructure supervisor at Southeastern Med. “Datawatch unlocks and prepares the data quickly and easily, and with the new ability to send data directly into IBM Watson Analytics, we think this opens up powerful cognitive computing based insights to a much wider range of users.”
“Datawatch’s intuitive self-service data preparation technology was specifically designed for the everyday business user and is a perfect complement to IBM’s modern business intelligence system,” said Michael Morrison, president and CEO of Datawatch. “Users can now spend their time in high-value analytic activities and harness the full power of IBM’s cognitive capabilities to derive new insights that have the potential to innovate and transform their business.”
Additionally, stop by Datawatch’s booth (No. 512) at the Gartner Business Intelligence & Analytics Summit, taking place March 14-16, 2016 in Grapevine, Texas or attend the 10:45 a.m. session on March 14 regarding the “New Advances in Self-Service Data Preparation.”
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.
1 Forrester Blog, 3 Ways Data Preparation Tools Help You Get Ahead Of Big Data, February 2015: http://ibm.biz/Bd4DJm
2 The Forrester Wave™: Big Data Hadoop Solutions, Q1 2014, http://ibm.biz/Bd4DJC
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