Infosys Invests $5.5M in Automated Data Discovery Startup Waterline Data Science
The second investment of $1.5 million is expected to be completed by 6 April, 2018
Infosys announced on 22 March, 2018, it has made a follow-on investment of $1.5 million through the Infosys Innovation Fund in Waterline Data Science, a leading provider of data discovery and data governance software. Infosys had made an initial investment of $4 million in the startup in January 2016.
Waterline Data Science provides data scientists and business analysts a self-service data catalog to help discover, understand and provision data, and an automated data inventory that enables agile data governance across metadata, data quality and data lineage. Founded 2013, Waterline Data’s total funding raised is a reported $24.5 million from investors like Partech Ventures, Menlo Ventures and Jackson Square Ventures.
The investment of $1.5 million is expected to be completed by 6 April, 2018, subject to necessary approvals.
“We see a need for automated data discovery solutions like Waterline Data Science in helping our clients achieve greater business value from their Big Data assets. This investment underscores our commitment to our clients to bring innovative data science solutions across our platforms and offerings,” said Ritika Suri, senior vice president of corporate development at Infosys.
“We are proud to partner with Infosys, a global leader in next-generation services, to help enterprises scale self-service and data governance for smart data discovery. We believe that this partnership will provide significant value to our customers as we combine the Waterline Data Science offering with Infosys’ global presence and broad industry expertise,” said Alex Gorelik, founder and chief executive officer of Waterline Data Science.
CEO of Waterline Data, Gorelik, writes in a blog that, “[according to Gartner] data cataloging projects will fall short of their full potential if data and analytics leaders can’t tie them to broader data management needs. There is simply too much data for humans to do this on their own. If data-driven organizations want to compete, they will have to embrace automatic discovery or they will very quickly discover they have fallen behind the pack”.
Gorelik who further predicts that cloud migration will become compulsory not an option further writes, “Broad adoption of the cloud will finally force object stores to be hardened and properly governed. This means more data will be used to drive value and monetization”.
The next few years to come will see the rise of one corporate role. According to Gorelik, “I see more large enterprises adding Chief Data Officers (CDO) every year. The new development will be turf wars with Data Protection Officers. With competing objectives, these important data professionals will have to grapple with age-old problems of governance versus agility”.
Officers in charge of trying to protect data and not expose it to too many outside sources, will clash with officers trying to leverage the same data by sharing it with outside sources. “Defense will keep you on the right side of the compliance and allow you to stay in the game, but if an organization is only looking at how not to get hurt, well, it’s going to get hurt by not making the moves that will put it ahead. CDOs know there’s new revenue and cost cutting to be had, but they’ve been too distracted with defensive maneuvering. This will change now that more organizations are moving from getting their data houses in order to converting their fully governed data into actionable intelligence. After all, what’s the point of Big Data if it’s not helping your business make money?”
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