Business intelligence is in a period of generational flux. This book is a welcome addition to our understanding of the changes that are clearly underfoot.
The definition of business intelligence is difficult to pin down and often runs to more than a lengthy paragraph. Perhaps the most concise definition appeared with what might have been the first use of the term in the October 1958 issue of the IBM Journal of Research and Development by Hans Peter Luhn:
The ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.
“Presented facts” are presumably extracted from data—in business, this almost always means transaction data housed in enterprise systems such as enterprise resource planning, customer relationship management, and supply chain management. “Action” in business implies decision making, so the role of “guide” is to improve or enhance decision making toward the “desired goal” of improved performance, effectiveness, efficiency, profitability, or other goals.
In its first decades, business intelligence (BI) was often muddled together with decision support systems, and the information and communication technology platforms to support both were quite similar. As noted, the information, or perhaps knowledge, extracted from the data came almost entirely from processing transaction data, and for good reason. Transaction data is internal; it is about “us,” not “them,” so we have it in our databases in well-structured ...