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Datawatch Brings “Data Socialization” to Self-Service Analytics

Datawatch_logoDatawatch Corporation (NASDAQ-CM: DWCH) announced its strategic vision and product road map for making “data socialization” a reality for all business users of self-service data preparation. Currently in beta, the next addition to the Monarch family will include all of the self-service data preparation benefits for which the product is highly regarded, and, in a first, add key attributes common to social media platforms. This powerful combination will enable data scientists, business analysts and even novice business users across a company to search for, share and reuse prepared, managed data to achieve true enterprise collaboration and agility, resulting in better and faster business decisions.

Datawatch invented self-service data preparation. Its Monarch product has been used in more than 40,000 organizations to unlock all data, including “dark data” such as PDF reports, web pages, log files, and streaming and multi-structured data. Capitalizing on the largest installed base of data preparation users and unmatched expertise supporting the largest enterprise deployments, Datawatch is applying its unique experience and market position to now deliver a compelling data socialization roadmap starting this quarter.

Introducing Data Socialization

Social media platforms have dramatically increased end user expectations about the availability and timeliness of information. Users increasingly have these same expectations for business information, regardless of where the data resides or how it’s formatted. The roadmap for Datawatch Monarch will deliver data throughout the enterprise with many of these same attributes. Key features will include:

  • Cloud-Based Data Preparation – Deliver data preparation and access to everyone, everywhere.
  • Collaboration – Understand the relevancy of data in relation to how it’s utilized by different user roles in the organization (e.g., sales operations or internal auditing); follow key users and data sets; and collaborate to better harness the “tribal knowledge” that too often goes unshared.
  • Crowdsourcing – Leverage user ratings, comments and popularity to make better decisions about which data to use.
  • Information Marketplace – Browse a centralized catalog of all relevant internal and external data.
  • Intuitive Search – Search cataloged data, metadata and data preparation models indexed by user, type, application and unique data values to quickly find the right information.
  • Machine Learning – Benefit from machine learning capabilities, which identify patterns of use and success, perform data quality scoring, suggest relevant sources, and automatically recommend likely data preparation actions based on user persona.
  • Data Quality and Governance – Provide sanctioned, curated data sets to promote reuse and consistency. Comprehensive governance features, including data masking, data retention, data lineage and role-based permissions, are necessary to uphold corporate and regulatory compliance and enhance trust in data, analytics processes and results.

This new, major release is specifically designed to meet the needs of three key constituencies: IT, analysts and information workers,” said Jon Pilkington, chief product officer at Datawatch. “The IT team will benefit from required data governance and will be able to deliver more value to a wider variety of business users. Analysts will be more productive, with the ability to acquire and prepare data from any source, and they can now remove all of the redundant work across different silos. And information workers who use data daily to make business decisions, but often lack the technical skills to access and prepare data, will no longer be left out of the process. Our strategic road map for data socialization will make the next-generation of Monarch an essential part of the decision-making fabric for all analytical and operational processes.”

Product Availability

The product is in beta release with early adopters. General availability is expected in December 2016.

 

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