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Datawatch Achieves APAC Channel Hyper-Growth as Resellers Deem Monarch Best Data Prep Tool for Tableau Customers - Company solidifies partnerships with six more Tableau resellers and boosts channel revenue in the region by 56 percent in 1H16 - Datawatch.com
Datawatch Achieves APAC Channel Hyper-Growth as Resellers Deem Monarch Best Data Prep Tool for Tableau Customers

 

NewswireTODAY - /newswire/ - Bedford, MA, United States, 2016/07/26 - Company solidifies partnerships with six more Tableau resellers and boosts channel revenue in the region by 56 percent in 1H16 - Datawatch.com. NASDAQ-CM: DWCH

   
 
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Datawatch Corporation today announced 56 percent year-over-year growth in APAC channel revenue in 1H16. The company’s high-growth trajectory is in part attributed to burgeoning market demand for Datawatch Monarch as the best self-service data preparation (prep) platform for Tableau users. The company attracted six more prominent Tableau resellers in the region in just the past four months. Partner organizations from India and China to the Philippines are recognizing Monarch for the unique value it provides customers in speeding and broadening analytics, and being a profitable means to expand their respective businesses.

To date, Datawatch has forged channel partnerships with more than 50 organizations across the APAC region, nine of which are Tableau resellers. DFOCUS Co. Ltd. in South Korea, Malaysia-based Strateq Group, and NTT Data Business Solutions Pte Ltd. in Singapore were the first Tableau resellers to join Datawatch’s partner program. In 1H16, Datawatch signed: Business Applications Co. Ltd. (Thailand), Data Knowledge Management Ltd. (Greater China), Corporate Renaissance Group (India), JardineOne Solution (HK) Ltd. (Hong Kong and Macau), PT Pervasif (Indonesia) and MISNet (Philippines).

Datawatch Monarch enables data analysts and business users to quickly acquire, manipulate, blend and prepare data from virtually any source without having to rely on IT for data access or specialized reports to feed into analytics and visualization tools. The self-service data prep platform is robust and offers cutting-edge capabilities, yet it’s unmatched in ease-of-use, making it a perfect complement to Tableau.

“One of the major pain points for some of our clients is being able to quickly source, blend and wrangle data to gain new insights,” said Vijay Jog, founder and president, Corporate Renaissance Group. “This is especially important as the volume of data continues to increase. Our partnership with Datawatch allows us to provide our clients with a cost-effective solution that addresses this need and enables us to serve as their go-to solutions partner. We look forward to a very fruitful partnership with Datawatch. We love the solution.”

With Datawatch, Tableau resellers are empowering customers to prep less and analyze more. The solution gives organizations the ability to tap the underlying data they need to maximize the business insights they can gain from the Tableau platform. Among other things, Monarch enables users to:

• Automatically extract and use data from multi-structured, semi-structured and unstructured sources, such as text reports, web pages, PDF documents, JSON and log files so they can finally use the data locked in SAP, Cognos, legacy or any application;
• Access and blend data from all databases, Salesforce, Hadoop, NoSQL and other sources;
• Manipulate and enrich data with a simple point and click;
• Export prepared data directly to a Tableau TDE or publish to Tableau Server.

“If we lived in a perfect world, our customers’ data would be neatly lined up into labeled rows and columns of strings and numbers,” said Eric Natividad, president and CEO, MISNet. “But the reality is that we have a report here, a PDF there most of it being what the industry calls ‘dark data.’ We are positive that Datawatch Monarch is the secret sauce that can help our customers draw more insights from their data through self-service data prep and, eventually, data visualization.”

“Datawatch Monarch is in high demand worldwide as a powerful standalone self-service tool for radically accelerating organizations’ time-to-analysis, as well as addressing operational use cases,” said Tim May, APAC business development director, Datawatch. “Monarch is the only data prep platform that provides the agility Tableau customers and other business users want, while delivering the governance and control IT requires. The traction we’re seeing in APAC is indicative of that value, as well as the tool’s unmatched ability to help organizations unlock and use all of their data, including dark data, to significantly broaden analysis.”

For questions specific to Datawatch’s APAC partner program, please email: apacpartners[.]datawatch.com.

About Datawatch Corporation
Datawatch Corporation (datawatch.com) 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.

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.

© 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.

 
 
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Datawatch Achieves APAC Channel Hyper-Growth as Resellers Deem Monarch Best Data Prep Tool for Tableau Customers

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Datawatch Monarch |
Contact: Amanda Beaupre - Datawatch.com 
978-275-8387 amanda_beaupre[.]datawatch.com
 
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IMPORTANT INFORMATION: Issuance, publication or distribution of this press release in certain jurisdictions could be subject to restrictions. The recipient of this press release is responsible for using this press release and the information herein in accordance with the applicable rules and regulations in the particular jurisdiction. This press release does not constitute an offer or an offering to acquire or subscribe for any Datawatch Corporation securities in any jurisdiction including any other companies listed or named in this release.

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