Most people now realize the massive opportunity advanced analytics can unlock for business, that is, the ability to drive significant top- and bottom-line impacts and help embed intelligence capabilities throughout the organization. Untold companies have spent millions of dollars to build data science practices, as well as the associated analytics infrastructure to support them.
Business leaders often struggle to understand the value of data science, however, because they’re unable to operationalize the insights they glean from their analytics/data science activities. At many companies, data science teams generate tremendous analytical insights, but they struggle to move those insights quickly from the data lab environment to production, at scale—in what might be thought of as an industrialized method. They can’t reap intelligence from information and make that data intelligence pervasive.
Enter AnalyticOps—which combines processes and tools to address the gap from insight to pervasive intelligence and realized value. AnalyticOps is the “productionalization” of analytics: bringing analytics from theory and numbers to production and value. It is a systematic approach that drives automation, standardization, and governance to unlock the value inherent in your organization—and it does this at scale.
AnalyticOps sounds like a buzzword. Everyone talks about it even if they don’t really ...