Final answer:
Data preprocessing involves three tasks: data cleaning, data transformation, and data integration.
Step-by-step explanation:
Three Tasks of Data Preprocessing:
Data Cleaning: This involves handling missing values, inconsistent data, and noisy data. It may include techniques such as imputation, outlier detection, and removing duplicates.
Data Transformation: This step involves transforming data into a suitable format for analysis. It may include tasks like normalization, discretization, and encoding categorical variables.
Data Integration: This task involves combining multiple datasets into a consistent and unified format. It may require resolving inconsistencies, merging data, and handling duplicates.
These tasks are crucial in preparing data for analysis and ensuring its quality and usability.