Which CPMAI phase is primarily responsible for turning raw data into model-ready datasets?

Which CPMAI phase is primarily responsible for turning raw data into model-ready datasets?

• A. Deployment
• B. Monitoring
• C. Data Preparation
• D. Data Understanding

Answer: (C)

Data preparation is the step that turns raw data into model-ready datasets. It involves cleaning the data, handling missing values, normalizing or encoding features, and performing feature engineering to create meaningful inputs for the model. It also includes organizing the data into the appropriate shapes and splits (training, validation, test) that modeling algorithms require. Data understanding helps you assess what data exists and its quality, informing what needs to be cleaned, but the actual transformation into a usable dataset happens during preparation. Deployment and monitoring come later in the lifecycle and deal with using the model in production and tracking its performance, not the data shaping itself.

Data preparation is the step that turns raw data into model-ready datasets. It involves cleaning the data, handling missing values, normalizing or encoding features, and performing feature engineering to create meaningful inputs for the model. It also includes organizing the data into the appropriate shapes and splits (training, validation, test) that modeling algorithms require. Data understanding helps you assess what data exists and its quality, informing what needs to be cleaned, but the actual transformation into a usable dataset happens during preparation. Deployment and monitoring come later in the lifecycle and deal with using the model in production and tracking its performance, not the data shaping itself.