From efficiency and effectiveness, we transition to insight and intelligence. The focus in this chapter is on the quantum of unstructured data at our disposal and the need for a contextually relevant framework to uncover intelligence from such information. We begin by highlighting the information overload prevalent today. We examine why timely access and analysis of information is important. And we discuss why the value of differential information is the key competitive factor in most industries.
We then proceed to discuss the popular methods for creating machine intelligence and knowledge representation. We point out why “black box” methods are unlikely to be widely accepted. We present a framework that can enable machine learning and knowledge representation in a contextually relevant, traceable manner. We end the chapter with lists of several real world applications that are in use today by thousands of people.
For the reader with a technical background, further technical details on the various methods for machine learning beyond the overview provided in this chapter can be found in the references at the end of the chapter.
What do we mean by “big data”? Why is there so much hype about big data? What opportunities does big data afford enterprises?
Digital Intelligence Today (2013) reports the following facts about the digital world: