What is CRISP-DM and how is it relevant to CPMAI?

• A. CRISP-DM is a data mining process model
• B. CRISP-DM is a data mining process model; CPMAI can adapt its stages to AI project lifecycle focusing on business understanding, data, modeling, evaluation, deployment
• C. CRISP-DM is a software development framework
• D. CRISP-DM is a hardware standard

Answer: (B)

CRISP-DM is a data mining process model that provides a structured, repeatable lifecycle for turning business problems into data-driven solutions. It guides you from understanding the business goal, through data understanding and preparation, into modeling, evaluation, and deployment, with feedback loops to refine work.

In CPMAI, this framework is relevant because AI projects benefit from a disciplined lifecycle that keeps the work aligned with business aims and real data. Adapting CRISP-DM to AI means mapping its stages to the AI project lifecycle: start with business understanding, then focus on data, proceed to modeling, evaluate the results, and deploy the solution. This helps ensure the project remains goal-focused, data-driven, and producible in real environments. Data preparation is typically integrated within the data and modeling phases as needed, rather than treated as a separate, standalone step.

The other options aren’t correct because CRISP-DM is not a software development framework or a hardware standard; it specifically addresses data mining and analytics processes.