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Independent Study by Forrester Research Finds that Data Catalogs Essential for Data Governance and Insights but Under Deployed

Mountain View, Calif. — August 1, 2019 — Waterline Data, a global leader in data cataloging solutions and applications, today announced the results of Machine Learning Data Catalogs Put The Entire Business In Full View, a commissioned study conducted by Forrester Consulting on behalf of the company to measure the effectiveness of machine learning data catalogs (MLDCs) in the enterprise. According to the research published in August 2019, MLDCs are deployed by only 35% of companies, despite the fact that 96% of organizations that have deployed the technology feel it delivers on their top data priorities. However, the survey discovered that awareness of and demand for MLDCs are growing — half of those surveyed plan to implement the technology within the next 12 months. At the same time, more than 75% of firms will have moved or plan to move their big data systems to the cloud.

“Machine learning data catalogs have emerged as key to a modern data strategy,” the study reads. “Firms that have adopted MLDCs have not only improved their security and compliance mandates, but they’ve also gained a better understanding of the data that can drive insights and actions.”

Enterprises Report Their Biggest Data Priorities and Challenges

Forrester Consulting surveyed 206 analytics and insights decision-makers employed by organizations based in the U.S. and the EU, most of them with at least $1 billion in revenue. While data security and privacy are top of mind at 65% of companies, only 35% say their current tools are helping them fully understand what data is available, putting their ability to protect data at risk. When asked about their top business priorities as it relates to data, 49% of organizations surveyed pointed to improving customer experience. Unsurprisingly, GDPR compliance is a higher priority for European organizations (40%) versus those based in the U.S. (29%).

“As the variety, volume and complexity of data continues to explode on a massive scale, it is absolutely critical that organizations adopt the tools that can help them manage the big data firehose not only for security and compliance but for the insights that can deliver improved customer service and overall competitiveness,” said Waterline Data CEO Kailash Ambwani. “As the study from Forrester Consulting shows, MLDCs are proving to be a key enabler of any successful data operation.”

MLDCs Proven to Boost Data-Driven Competitiveness

By comparing responses from organizations with and without MLDCs, Forrester Consulting discovered that organizations with MLDCs are able to resolve many of the challenges that weigh down their data operations:

  • 1.5x are better positioned to have full visibility of their business, put regulatory challenges to rest, and put their competitors on their heels
  • 1.5x are more likely to say their big data projects perform above expectations
  • 1.4x are more likely to deliver on their security and privacy needs
  • 1.4x are more likely to understand what data is available

 

Full Forrester Consulting survey results can be viewed here. Register here to attend a webinar on the study’s findings on September 18th.

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 and patented fingerprinting technology 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 www.waterlinedata.com, Twitter or LinkedIn.

Enterprise data leaders interested in seeing Waterline Data in action can register for a personalized live demo here.