Labeled data brings machine learning applications to life

Over the years, the types and quantity of analytics data have evolved, along with the repositories in which the data is stored. Data warehouses were bumped from center stage by big data systems better-suited to storing new forms of data, such as social media posts and machine logs. However, the refined data found in data warehouses may have a big role to play in machine learning and AI initiatives. In this Q&A, Svetlana Sicular, a research VP at Gartner, says that simply coupling AI and data together doesn't make for the magic wand that some people think it will. Sicular provides an overview of the past and present of data stores and discusses how transactional and labeled data can provide useful information for AI and machine learning applications.