Value Engineering: The Secret Sauce for Data Science Success

This chapter entails Bill Schmarzo's Data Science Value Engineering Framework, a process that starts with a thorough understanding of the organization's key business initiatives, or what the organization is trying to achieve from a business or operational perspective. The Data Science Value Engineering process identifies and interrogates the key stakeholders to identify their top priority use cases (clusters of decisions around a common subject area) that support the business initiative. Once you have identified, validated, valued, and prioritized the use cases, then the supporting data, analytics, architecture, and technology requirements fall out as a consequence of the process.
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