Machine learning: Tackling the 'big' in Big Data - SD Times

Big Data is becoming too big to manage manually. The amount of data coming from sensors, streams and social media is astronomical--but that's only part of the problem. Out of all the data that is being collected, only a small amount of it is actually essential, making it an impossible task to find the needle (value) in the haystack (data). "Data collection is easy," said Sri Ambati, CEO of H2O.ai, a machine learning solution provider. "But it is not just about collecting data for your customer anymore; it is knowing what they want that makes a big difference." In order to sift out the value from all the data, organizations are turning to machine learning technologies to learn from their data, make sense of their data, and make better business decisions based on the data. "Machine learning is the crucial link between business use, between applications at the business level, and between ROI to the actual collection of data," said Ambati. Big Data has become the norm in today's enterprise, and machine learning is now becoming imperative to that norm, according to Steven Noels, cofounder and CTO of NGDATA, a Big Data analytics and management provider. Businesses need to continuously pull insights out of their massive amounts of data in order to improve customer experience, streamline business processes, optimize solutions, and understand the business in real time.