by Angela Guess
Ben Rossi recently wrote for Information Age, “A recent Gartner survey found that more than 75% of companies are currently investing or planning to invest in big data initiatives over the next two years. This heightened interest has led analysts to speculate that big data project investments will reach $242 billion in short order. When it comes to big data, the real opportunity for enterprises is in advanced data analytics, specifically machine learning. With this methodology, big data can be mined to automatically uncover business insights as well as generate predictive models.”
Rossi goes on, “The ultimate scenario is one where machine learning can accurately guide forward-looking business decisions and reveal patterns never before seen. It is this promise of delivering accurate, actionable, predictive information that will drive machine learning to play a greater role in big data analytics, and make 2016 the start of the age of enlightenment for high-performance machine learning.”
He continues, “Machine learning is a fundamental tool in creating a world that can sense and react to dynamic, distributed phenomena. The number of variables and factors that can be taken into consideration by this methodology is unlimited. It weaves together real-time data collection with the automation of business processes, and is ideally suited to deal with complex, disparate data sources and the high number of variables involved in data sets that are large, diverse and fast changing. In other words, machine learning is primed to handle big data.
photo credit: Flickr/ sacks08