CHAPTER 5Roadmap for How to Implement AI-Enabled Analytics in Business
Success is not final, failure is not fatal: it is the courage to continue that counts.
—Winston Churchill1
With the fundamentals of analytics in place and an enlightening discussion on human decision-making to espouse why analytics are essential, we now come to the core: the Roadmap to implement AI-enabled analytics. This chapter will deliver, in great detail, the “how to” for implementing a culture of data-driven decisions for improved business performance.
Geoffrey Moore, the famed organizational theorist and author of the book Crossing the Chasm, wrote, “Without big data analytics, you are blind and deaf and in the middle of a freeway.”2 As we shall now expound, it takes more than big data analytics to obtain the value of insights from data; it takes a culture about analytics; that is, it is one thing to reveal insights, and another to actively use them.
Insights are distinguished from data and information. As presented in Figure 5.1, data is simply the raw values collected from data sources. Information results from arithmetic manipulation, however small, that tells us more than the raw values. For example, subtracting the values of last year's sales year-to-date against this year's sales informs whether year-over-year sales have increased or decreased. This is information from data. But when AI-enabled analytics is applied on data, insights are obtained that reveal something that we do not know about ...
Get AI-Enabled Analytics for Business now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
