Under the CRISP-DM process for data analysis, ________ is the process of applying algorithms to data to seek out, identify, and display patterns or messages found in the data.

• A. Modeling
• B. Data Cleaning
• C. Evaluation
• D. Deployment

Answer: (A)

Modeling is the phase in CRISP-DM where you take the prepared data and apply algorithms to uncover patterns or messages. This step involves selecting suitable modeling techniques, training and tuning models, and generating results that reveal structure such as clusters, predictions, or decision rules. The goal is to build and compare models that explain or predict the data, and to present the patterns they uncover. For context, data cleaning happens in data preparation, focusing on cleansing and transforming data; evaluation checks how well the models perform against criteria; deployment puts the chosen model into production. For example, you might use clustering during modeling to group similar customers and then visualize those groups to interpret the patterns.