SnapLogic designed its cloud-based data integration management platform as a service about 17 years ago, with usability and self-service as primary design mandates. “Our platform has a graphical user interface in which users can work on a digital canvas and snap together modules to create a pipeline for data management, analytics, and data transport,” said Michael Nixon, SnapLogic’s VP of cloud data marketing. “In keeping with the concept of data mesh, business units can own their own data, with role-based access, security policies, and other controls.” AI, introduced into the SnapLogic product line 7 years ago, can be used to recommend “next steps” in building out integrations. This has been recently enhanced further with SnapLogic releasing SnapGPT, its large language model interface.
An underlying premise of data mesh is that business units should be able to control their own data and interact with one another by sharing data. “A data product that is created to run analytics for one business unit might be useful to another,” Nixon continued. “For example, the sales department might have a module that marketing would be interested in. With the right permissions, marketing could access it to use as is or run additional analytics.” The output of the data product could also be used to drive other operational aspects of the business.