Business intelligence will move beyond dashboards, and AI and machine learning will become easier for less skilled workers as augmented analytics are embedded into platforms. Enterprises struggling to get their data management and machine learning practices up to speed in an era of more and more data may be in for a nice surprise. After years of bending under the weight of more data, more need for insights, and a shortage of data science talent, augmented analytics is coming to the rescue. What's more, it could also help with putting machine learning into production, something that has been an issue for many enterprises. Identified as a major trend by Gartner at its Symposium event last year, augmented analytics has been around for several years already, according to Rita Sallam, distinguished research VP and Gartner fellow.

Machine Learning is the buzzword of the moment. In recent years, news stories raving about its possibilities have soared, Google searches for the term have quadrupled, and companies across the globe have been scrambling to figure out how to capitalize on the excitement by bringing it into their product mix. While that can be a great thing, claims made by some businesses about what Machine Learning can do are wildly exaggerated. That makes it crucial to cut through the noise and get to grips with its potential, limitations, and what you can realistically achieve with your resources so that any investment makes solid business sense -- so say Philip Lima, CEO of Mashey, and Boaz Farkash, Head of Product Management at Sisense. The pair joined forces to deliver an in-depth webinar on Machine Learning and business intelligence, which you can view in full here.