Final answer:
In CRISP-DM's Data Preparation phase, tasks include data cleaning, constructing data, data integration, and data transformation, all of which make the dataset suitable for mining in the subsequent phase.
Step-by-step explanation:
The Data Preparation phase in the Cross-Industry Standard Process for Data Mining (CRISP-DM) is a critical step where data is transformed and readied for the modeling phase. This involves several tasks such as data cleaning, constructing data, data integration, and data transformation. Data cleaning is about correcting or removing inaccurate records from the dataset.
Constructing data may involve creating new attributes that might be helpful for mining. Data integration is combining data from multiple sources, and data transformation involves normalizing or scaling data so that it's in a format suitable for data mining. This phase ensures that the datasets are robust, relevant, and structured to provide high-quality inputs for the subsequent modeling phase.