Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners

PART TWO Turning Data into Business Value

This second part of the book shifts from the storage of data, preparation of data, hardware considerations, and the software tools needed to perform data mining to the methodology, algorithms, and approaches that can be applied to your data mining activities. This includes a proven method for effective data mining in the sEMMA approach, discussion about the different types of predictive modeling target models, and understanding which methods and techniques are required to handle that data effectively. From my experience, most business environments use several people to perform each of the tasks. In larger organizations, the tasks might be split across many groups and organizationally only meet at the executive level of the organization. A quote from Shakespeare that I have always appreciated to introduce this topic is:

If you can look into the seeds of time, And say which grain will grow and which will not, Speak then to me, who neither beg nor fear Your favours nor your hate.

—Macbeth, Act 1, Scene 3

This verse shows an appreciation and understanding from hundreds of years ago that those people who can predict future behavior have a distinct advantage regardless of the venue. In sports, this is often call field presence: the talent some players have to effectively anticipate where the ball will be played and be there before the ball arrives. On Wall Street, fortunes are won by correctly anticipating the movement of the market in ...