Cognitive Computing and Big Data Analytics

CHAPTER 10 The Process of Building a Cognitive Application

Organizations in many different industries are in the early stages of developing cognitive applications. From healthcare to manufacturing to governments, decision makers need to quickly make sense of large volumes and varieties of data. Problem solving often requires the aggregation of a multitude of disconnected data sources including a combination of internal and external data. In addition, it is increasingly likely that the data required to answer problems or deliver new insights is unstructured—such as text, videos, images, sound, or sensor data. Valuable insights may remain hidden because the volume, variety, and velocity (speed) of the data are so hard to manage. Organizations are now beginning to recognize the potential benefits of using cognitive applications to find the patterns in data that can help to improve outcomes.

Chapters 11–13 provide examples of emerging cognitive computing applications across multiple industries. Although the domains and applications described in these chapters differ, certain common attributes of each situation make them a good fit for cognitive applications. Organizations that are implementing cognitive applications typically face similar challenges regarding data and the decision making process such as:

• Large volumes of unstructured data that must be analyzed to make good decisions.
• Decisions must be based on constantly changing data, new sources, and forms of data.
• A significant ...