The CRISP$-$DM Process, SEMMA Process, KDD Process, and the SAS Analytics Life Cycle are all methodologies used in data analytics projects. Which of the following best describes a common similarity among these methodologies?

Question $25$ options:

a$)$

Exclusive focus on model deployment: Each methodology emphasizes only the deployment phase of analytical models, disregarding the importance of understanding business problems and data preparation.

b$)$

Ignoring model evaluation: Model evaluation is considered unnecessary in these methodologies, with an assumption that any model developed will perform adequately on real$-$world data.

c$)$

Emphasis on data preparation and understanding: All methodologies prioritize data preparation and understanding the business problem as crucial steps before model building and deployment.

d$)$

Sole reliance on proprietary software tools: Each methodology is tied to specific proprietary software tools, making them inapplicable in environments where those tools are not available.

e$)$

No iterative process: They advocate for a linear process without any iterations, assuming that the first solution developed will always meet the project's objectives without the need for revisions.