Latest Release combines flexible, intuitive prep with predictive scoring, enabling organizations to harness the power of their best business and data science minds with ease.
BEDFORD, Mass., Dec. 11, 2018 (GLOBE NEWSWIRE) — A major issue facing enterprises today is how to leverage advanced and predictive analytics on a large scale while data scientist resources are scarce. Datawatch Corporation (NASDAQ-CM: DWCH) today announced the release of Datawatch Swarm 2.2, which addresses that problem by delivering built in automation that connects data scientists with business analysts to better scale advanced analytics across the entire organization without increasing headcount. The integration between Datawatch Swarm and Datawatch Angoss, the powerful predictive and data science platform, creates the industry’s only enterprise data intelligence marketplace that acts as a virtual exchange of trusted data and an execution environment for every data role in an organization.
“Forward-thinking enterprise data teams that support their organizations with strategy, structure and tools are on a mission to achieve better cross-functional use of data amidst increasingly scarce data science resources,” said Rami Chahine VP of Product Management Datawatch. “Our latest release of Datawatch Swarm allows them to build forward-looking predictive analytics that enable businesses to become more data savvy and make use of data science resources for all critical business decisions. Businesses can now leverage in-house data science resources more effectively, enabling better collaboration between data science teams and lines of business.”
Datawatch Swarm empowers every individual, department and organization with advanced intelligence and insight into how data can be used to drive further team collaboration, socialization and support of data governance practices.
“Data and analytics leaders are well aware of the benefits data science and machine learning can provide, but have been constrained by the need for data scientists to control the analytics workflow, delaying time to value,” wrote Joao Tapadinhas, VP, Business Analytics and Data Science, Carlie Idoine, Sr Director Analyst and Austin Kronz, Associate Principal Analyst at Gartner.*
In a recent Gartner report titled How Citizen Data Science Can Maximize Self-Service Analytics and Extend Data Science*, analysts Joao Tapadinhas, Carlie Idoine, and Austin Kronz highlight the following recommendations for data and analytics leaders pursuing analytics and business intelligence (BI) modernization:
- Expand the variety of data accessible for analysis by facilitating ingestion, preparation and analysis of complex data sources that are currently beyond the reach of analysts and business users.
- Increase the range of analytics capabilities available to users by deploying tools in areas such as data preparation, self-service analytics and augmented analytics.
- Make advanced analytics accessible to a wider audience by embracing the role of the citizen data scientist.
Offered as either a cloud or on-premises data intelligence platform, Datawatch Swarm was designed to make data more accessible across an organization and increase the range of analytics capabilities for users of any skill level. With this latest release, Datawatch Swarm now improves the accessibility of advanced analytics by leveraging scare data science resources and models more effectively, and giving data scientists easier access to curated, trusted data sets from the line of business users who possess the context.
“We’re breaking down barriers to insight with this solution, and even your basic day-to-day decisions can now be made with tremendous levels of confidence,” continued Chahine. “No other solution makes collaboration between data science teams and the business this easy.”
Datawatch Swarm is designed to connect everyone within the organization with the intent to turn data into insights, bringing more minds together on more decisions to generate more trust. Newest features in this release include:
- New Graphical Flow-based UI — A completely re-designed visual experience makes Swarm the only analytics solution on the market that allows users to work with data in a spreadsheet-like grid view, or a graphical flow view. Users can toggle back and forth between the views to quickly and easily navigate their workspaces. The UI is approachable and intuitive for all users, regardless of their background and experience with other data platforms.
- Greater Collaboration and Controls— Allows businesses to easily connect data scientists with the lines of business in a controlled, compliant workspace that scales advanced analytics resources and skill sets across the entire organization.
- Detailed Information Cards — Users have more trust in their data thanks to information cards that deliver the granular history on every data asset, making it easier to understand where data came from and how it has been transformed and used.
- Advanced Automation — More robust, trigger-based automation makes it easier for enterprises to ensure the workspaces and outputs are always based on the latest, most trusted information, by automatically rerunning reports when new data is made available.
- More Connected Data Sources — Business users see a more complete picture with the ability to connect to more data sources including Google, Tableau, and Sharepoint along with a number of new custom connectors for SAP HANA, AWS Redshift, Teradata and Cloudera
*Gartner, How Citizen Data Science Can Maximize Self-Service Analytics and Extend Data Science, 21 September 2018
About Datawatch Corporation
Datawatch Corporation (NASDAQ-CM: DWCH) is the data intelligence provider with market leading enterprise data preparation, predictive analytics and visualization solutions that fuel business analytics. Only Datawatch can confidently position individuals and organizations to master all data – no matter the origin, format or narrative – resulting in faster time to insight. Datawatch solutions are architected to drive the use of more data, foster more trust and incorporate more minds into business analytics. Thousands of 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, Toronto, Stockholm, Singapore and Manila. To learn more about Datawatch 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.
Media Contact:
Frank Moreno
Vice President Worldwide Marketing, Datawatch Corporation
frank_moreno@datawatch.com
978-275-8225
Twitter: @datawatch
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