New innovations in self-service data preparation technology are having a significant impact on a business user’s ability to unlock and use all data, including dark data. Earlier this year the Gartner Group called this “the next big disruption in business intelligence.” And with this newfound data comes the need to intelligently visualize and analyze it. This is where cognitive computing becomes the perfect complement.
The theme at the recent IBM World of Watson conference in Las Vegas was laser-focused on the world of Watson as it pertains to cognitive computing and artificial intelligence. Evolving from the information-on-demand focus of the past, the conference offered several exciting examples of how people are using technologies like Watson Analytics to change industries. It truly has the power to be transformative.
On Wednesday, October 26, IBM’s Chairman, President & CEO, Ginni Rometty provided the keynote address, A World with Watson, where she was joined by Mary Barra, the Chairman and CEO of General Motors and other executives. They spoke about how their different industries are being transformed by the possibilities provided by Watson Analytics. And, while it’s still early days, the possibilities that stem from artificial intelligence and cognitive computing – not to mention some big investments – are taking hold at organizations around the world.
At Datawatch, we know that the fuel for artificial intelligence and cognitive computing is information. In order to have major breakthroughs in areas like healthcare and auto manufacturing you need to be able to access and unlock all kinds of data so that it can then be processed and studied in technologies like Watson Analytics. These are exciting times, as there now seems to be a growing understanding around the value of bringing all kinds of data together – structured and unstructured. Companies need to tap this information in order to really harness the power of this next generation of data processing.
As analytics gets smarter about powering the citizen data scientist and a broader set of people, users will have access to deeper insights and understand not just what has happened but what is likely to happen. This is really big. Traditional BI has always looked at history to uncover what happened. Predictive analytics is about what is likely to happen based on those historical patterns. This next phase in the evolution of analytics will empower users to quickly understand what they should do about these patterns and identify the best actions to take based on that understanding.