Datawatch Monarch Swarm Brings Data Intelligence to Business Analytics
Update introduces personalized machine learning in a team-driven data preparation platform to optimize user agility and corporate data trust.
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Datawatch Corporation has released Datawatch Monarch Swarm, its intelligent enterprise data preparation and analytics platform that helps enterprises interact with and leverage their greatest assets: people and data. With new applications of machine learning technology to benefit every user no matter their skill level, Monarch Swarm empowers individuals, departments, and organizations with advanced intelligence and insight into how data can be used to drive further team collaboration, socialization, and support of data governance practices.
This release of the enterprise data preparation platform provides a bridge between IT governance and business analyst agility.
Offered as either a cloud or on-premises data intelligence platform, Monarch Swarm presents business users with a personalized experience for creating, accessing, validating, and sharing governed, trustworthy data sets and models to prevent the duplication of work and increase engagement of business users across the company. Among the platform's newest features:
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Team-driven data preparation allows companies to easily deploy centralized data preparation across teams, departments, and the entire enterprise in the configuration that works best for their infrastructure while reducing machine footprint and IT involvement and enabling data preparation and analytics from any machine, anytime, and anywhere.
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Advanced machine learning shortens the learning curve with detailed ranking and data recommendations so all users can benefit from data models and sets created by advanced users and data stewards. It also provides smart recommendations on relevant data sets and models along with suggested analytics guidelines for more powerful data preparation and analytics use.
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Evolved multistructured data capture brings the heritage and legacy of Datawatch Monarch to the browser. Users can automatically extract data from multistructured sources, including PDF documents, on any computer, anywhere.
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Sophisticated data connectors are offered for structured data sources related to enterprise applications including NetSuite; marketing-focused data sets from Google AdWords or HubSpot; and shared storage drives such as Microsoft SharePoint, Box, Dropbox, and Google Drive.
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Dynamic data socialization facilitates data collaboration on data sets, models, and content through ranking, rating, and commenting features, providing greater insight into how users employ information while avoiding duplication of analytics projects. It enables users to quickly and easily search across files and folders through various methods to find and use secure, governed data sets.
More information is available at www.datawatch.com.