• September 8, 2020

Segment Launches Data Lakes

Segment, a customer data platform (CDP) provider, today launched Data Lakes, a data architecture for storing large quantities of raw information that can then be used to create advanced analytics, uncover rich customer insights, and power machine learning and artificial intelligence initiatives.

"We all know that customer data creates a competitive advantage, but what companies sometimes fail to recognize is that the quality of their data architecture will determine just how significant that advantage really is," said Tido Carriero, chief product development officer at Segment, in a statement. "Segment Data Lakes gives data scientists the foundation they need to unlock the full potential of their customer data so they can build better products and provide world-class customer experiences."

"Segment Data Lakes has been an absolute game-changer for us. In fact, we no longer need a data warehouse, and we can query what we want, when we want, without worrying about costs," said Casey Kent, lead infrastructure engineer at Rokfin, a Segment customer, in a statement. "It's provided us with a foundation that gives us a much deeper understanding of our customers than ever before, and we've been able to use these insights to build a truly differentiated experience for our customers. We've generated new types of customer insights that we didn't think were possible."

"Customer data is essential to delivering exceptional products and experiences, but since data lakes are difficult to build and maintain, few businesses have the architecture in place to truly make the most of it," said Daniel Newman, a principal analyst at Futurum Research, in a statement. "As a data lake built specifically for customer data, Segment Data Lakes provides the foundation to unlock complex use cases like machine learning and advanced analytics, so businesses can do more with their data and power deeper personalization of the customer journey."

Segment Data Lakes is now available to Segment customers using Amazon Web Services (AWS). Support for Microsoft Azure and Google Cloud is planned.

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