Firms cash in on big data benefits
Firms that capitalize and analyze all relevant data and deliver actionable information could achieve an extra $430 billion worldwide in productivity benefits over their less analytically oriented peers by 2020, according to IDC.
The research firm predicts big data analytics technology investments will increase across Asia Pacific at 34% year over year in the next few years. This rapid growth in investment is creating a divide between the organizations that “know” and the ones that do not.
“The measure of information in our reality has been blasting, and investigating substantial information sets — supposed enormous information will turn into a key premise of competition, supporting new influxes of efficiency development, advancement, and customer surplus,” says Chwee Kan Chua, AVP for big data and analytics and cognitive computing at IDC Asia Pacific.
The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things (IoT) is expected to fuel exponential growth in data for the foreseeable future.
Another dimension that we are entering is a new period of computing history — the Cognitive Computing era. IDC predicts by 2020, 50% of all business analytics software will incorporate prescriptive analytics built into cognitive systems functionality.
“Cognitive Systems offer fundamental differences in how systems are built and interact with humans,” says Alon Anthony Rejano, associate market analyst at IT services research in IDC Philippines. “Cognitive-based systems are able to build knowledge and learn, understand natural language, and interact more naturally with human beings than traditional systems
Rejano said Cognitive Systems can quickly identify new patterns and insights and, over time, they will simulate even more closely how the brain actually works.
“In doing so, they could help us solve the world’s most perplexing problems by penetrating the complexity of big data and exploiting the power of natural language processing and machine learning,” he added.