Which CRISP-DM phase involves cleaning data, removing incomplete records, and selecting relevant attributes?

Which CRISP-DM phase involves cleaning data, removing incomplete records, and selecting relevant attributes?

• A. Data Preparation
• B. Deployment
• C. Evaluation
• D. Business Understanding

Answer: (A)

Data preparation is about getting the data ready for modeling. Cleaning the data, removing incomplete records, and selecting relevant attributes are the main tasks in this phase. Cleaning eliminates errors and inconsistencies, removing incomplete records reduces noise, and selecting relevant attributes focuses the dataset on what matters for the analysis. This helps improve data quality and model performance. In contrast, deployment involves putting the model into production and using it in real decisions; evaluation checks how well the model performs and whether it meets goals; and business understanding covers the problem definition, objectives, and constraints. Therefore, the described activities belong to the data preparation phase.

Data preparation is about getting the data ready for modeling. Cleaning the data, removing incomplete records, and selecting relevant attributes are the main tasks in this phase. Cleaning eliminates errors and inconsistencies, removing incomplete records reduces noise, and selecting relevant attributes focuses the dataset on what matters for the analysis. This helps improve data quality and model performance. In contrast, deployment involves putting the model into production and using it in real decisions; evaluation checks how well the model performs and whether it meets goals; and business understanding covers the problem definition, objectives, and constraints. Therefore, the described activities belong to the data preparation phase.