Cognitive Computing and Big Data Analytics

CHAPTER 6 Applying Advanced Analytics to Cognitive Computing

Advanced analytics refers to a collection of techniques and algorithms for identifying patterns in large, complex, or high-velocity data sets with varying degrees of structure. It includes sophisticated statistical models, predictive analytics, machine learning, neural networks, text analytics, and other advanced data mining techniques. Some of the specific statistical techniques used in advanced analytics include decision tree analysis, linear and logistic regression analysis, social network analysis, and time series analysis. These analytical processes help discover patterns and anomalies in large volumes of data that can anticipate and predict business outcomes. Accordingly, advanced analytics is a critical element in creating long-term success with a cognitive system that can ask for the right answers to complex questions and predict outcomes. This chapter explores the technologies behind advanced analytics and how they can be leveraged in a knowledge-driven cognitive environment. With the right level of advanced analytics, you can gain deeper insights and predict outcomes in a more accurate and insightful manner.

Advanced Analytics Is on a Path to Cognitive Computing

The role of analytics in an organization’s operational processes has changed significantly over the past 30 years. As illustrated in Table 6.1, companies are experiencing a progression in analytics maturity levels, ranging from descriptive analytics ...