Recognizing how Big Data Analytics projects are different

In Chapter 2, Creating an Opportunity Landscape and Collecting Your Gold Coins, we discussed the three major changes caused by Big Data Analytics—the ability to process all data and the ability to manage data disorderliness and allow correlation to trump causality. These fundamental shifts radically transform our ability to leverage technology. There are a number of differences between traditional technology projects and Big Data projects. Let us first examine some of the most notable ones.

Scope fluidity

Traditional technology projects usually start with a fairly definitive scope. The scope might change over a period of time, but at any given point of time, it is always quite well defined. As a result, we can develop specific schedules, plan for resources, and estimate costs and benefits. Big Data projects, however, typically start with an aspirational intent of some form of business outcome instead of a boxed scope. They are more...