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Waterline Data Founder’s New Book on Modern Data Lakes Reaches Best Seller Status

First Practical Handbook on How to Successfully Build and Run a Modern Day Data Lake Written by Alex Gorelik and Published by O’Reilly Media Draws on Real-World Examples from Leading Data-Driven Enterprises

Mountain View, Calif.—April 15, 2019Waterline Data, a global leader in data cataloging solutions and applications, today announced a new book, The Enterprise Big Data Lake: Delivering the Promise of Big Data and Data Science, published by O’Reilly Media and written by Waterline Data founder and CTO Alex Gorelik is now available. The book is a #1 New Release in the Data Warehousing category on Amazon.

After years of failure, data lakes have begun to regain some of their luster with the emergence of the cloud and other solutions that can help organizations more effectively manage them, but challenges and risk remain. The Enterprise Big Data Lake: Delivering the Promise of Big Data and Data Science guides managers and IT professionals from the initial research and decision-making process through planning, choosing products, implementing, maintaining, and governing the modern data lake. The publication includes best practices from some of the world’s leading data-driven enterprises, with essays from hands-on practitioners and industry experts on how to successfully architect and deploy a robust data lake. Readers will learn how to enable self-service to help users find, understand, and provision data; how to provide different interfaces to users with different skill levels; and how to do all of that in compliance with enterprise data governance policies.

The book leverages Alex’s 30-year career developing leading-edge data technology and working with some of the world’s largest enterprises on their thorniest data problems. Alex, credited with helping to launch the data catalog space, is the holder of two patents related to the unique Fingerprinting™ and automated tagging technology that powers Waterline Data’s AI-driven data cataloging solutions.

“Enterprises have been experimenting with using big data technology to build big data lakes for years, but many projects have stalled or failed outright because the approaches that worked at Internet companies need to be adjusted for the enterprise,” said Alex Gorelik, founder and CTO at Waterline Data and author of The Enterprise Big Data Lake: Delivering the Promise of Big Data and Data Science. “This book is based on hundreds of discussions with CDOs and other IT executives, data lake teams, data scientists, engineers, and data governance teams in both internet companies and traditional enterprises.”

As founder of three startups, Alex spent his career inventing cutting edge data-oriented technology and bringing it to market. Prior to Waterline Data, Alex served Informatica as GM of the Data Quality Business and SVP of R&D for Core Technology. He was also a Distinguished Engineer at IBM, which acquired his second startup, Exeros. The first company Alex founded, Acta Technology, was later acquired by Business Objects and is now marketed as SAP Business Objects Data Services. Prior to Acta, Alex managed development of Replication Server at Sybase and worked on Sybase’s strategy for enterprise application integration (EAI). Earlier, he developed the database kernel for Amdahl’s Design Automation group. He holds a B.S. in Computer Science from Columbia University School of Engineering and a M.S. in Computer Science from Stanford University.

Related links:

Click here to register for a new webinar that will be led by Alex on May 22: How DataOps Adds Value to Data Lakes.

Click here to purchase The Enterprise Big Data Lake: Delivering the Promise of Big Data and Data Science on Amazon.

Click here for the blog post on this topic.

About Waterline Data:

Waterline Data automates data discovery, compliance and the ability to take action on data by using a powerful combination of artificial intelligence, machine learning, ratings and reviews, and tribal knowledge to deliver an AI-driven 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, Twitter or LinkedIn.