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Waterline Data Named on Constellation ShortList™ for Third Straight Year

The Report Marks the Company's Fifth Appearance on a Constellation ShortList Since 2016

MOUNTAIN VIEW, Calif., Oct. 18, 2018 /PRNewswire/ -- Waterline Data, a global leader in data cataloging solutions and applications, today announced the company was named to the Constellation ShortList™ for Data Cataloging for the third straight year. It is the company's fifth appearance on a ShortList since 2016. Constellation evaluated over a dozen solutions and selected Waterline Data based on client inquiries, partner conversations, customer references, vendor selection projects, market share and internal research.

"We're excited to once again be recognized by Constellation Research's ShortList for Data Cataloging," said Kailash Ambwani, CEO of Waterline Data. "With the ability to automatically profile and tag billions of rows of data, the Waterline Data Catalog is the fastest and most scalable catalog available, allowing petabyte enterprises to quickly and accurately convert all of their mountains of data into faster, smarter decision making--a competitive must in today's data economy."

With data volumes and variety exploding, data catalogs are fast becoming an indispensable resource for data professionals and data consumers alike. The Waterline Data Catalog was specifically designed to resolve the challenges of high volume and high variety data by creating a real-time, virtual view of the enterprise's entire data estate even as new data pours in. The platform provides an easy to use "shop for data" interface to the enterprise's data estate to help business analysts use every day business terms find the data sets they need for self-service analytics without having to rely on IT.

With Waterline's automated discovery of data, organizations can leverage all the benefits of the cloud by providing a single point of governance to ensure data is findable, understandable, tracked and trusted. Enterprises can also quickly meet GDPR and other regulatory requirements while ensuring all data remains in a permanent state of compliance. Waterline works across an organization's entire distributed data estate, whether the data resides in the cloud, relational databases, on-premises or a hybrid environment.

"Best-of-breed catalogs search and serve up insights into available data assets in automated ways while also providing collaborative tools that enable users to comment on and enhance what is known about the value and usage of that data," said Doug Henschen, vice president and principal analyst at Constellation Research. "Data cataloging is important for any organization that wants to make the most of its data, particularly as data sources and data-driven applications multiply and as data scale and diversity grows."

Constellation advises leaders and teams on leveraging disruptive technologies to achieve business model transformation. Products and services named to the Constellation ShortList meet the threshold criteria for this category as determined by Constellation Research through client inquiries, partner conversations, customer references, vendor selection projects, market share and internal research. The Constellation ShortList is frequently updated as market conditions change.

About Waterline Data:
Waterline Data automates data discovery, compliance and the ability to take action on data by using a combination of artificial intelligence, machine learning, ratings and reviews, and tribal knowledge to deliver a Smart Data Catalog. Our customers spend less time searching for data and more time using it to derive value while complying with data governance mandates such as GDPR. The company is funded by Menlo Ventures, Jackson Square Ventures, Partech Ventures, and Infosys, and implemented in large enterprises around the globe. Founded in 2013, the company is headquartered in Mountain View, California. For more, visit us via www.waterlinedata.com, Twitter or LinkedIn.

Global Press Contacts:
Chris Blake
MSR Communications
Email: [email protected]

 

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SOURCE Waterline Data

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