CHAPTER 8Valuing Data with Statistical Analysis and Enabling Meaningful Access

“There are thousands of ways to mess up or damage a software project, and only a few ways to do them well.”

—Capers Jones

Applied Software Measurement: Global Analysis of Productivity and Quality

A business organization is not set up to be egalitarian. Certainly, when it comes to social interactions in the workplace, we should always show respect and be courteous to everyone. But organizationally, distinct roles and areas of responsibility require that boundaries be set. Regarding data access, organizational boundaries dictate appropriate permissions and privileges for each employee, determining what can be known and what can be acted on.

This chapter introduces approaches for accessing data determined by your role and responsibility. This includes data that has been valued and intentionally democratized or data that, by design, is not intended to be used as a democratized asset. Performing analytics and artificial intelligence (AI) drives the need for accessing data that is in direct support of the organizational demands for prediction, automation, and optimization.

Deriving Value: Managing Data as an Asset

While data, information, knowledge, and wisdom (DIKW) (discussed in Chapter 7, “Maximizing the Use of Your Data: Being Value Driven”) addresses the formation of a value chain, each point in each chain should be measurable so as to demonstrate value. If the data is to be regarded or treated ...

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