This video describes the data cleaning, integration, reduction, and transformation processes.
Data cleaning is the process of removing or cleaning incomplete, noisy, and inconsistent data through the use of data cleaning methods such as filling missing values, smoothing noisy data, removing outliers, and resolving inconsistent data.
Data Integration: Data Integration is the process of combining data from multiple data stores. We face some challenges while integrating the data, such as entity identification issues, redundancy and correlation analysis, Tuple Duplication, and data value conflict detection and resolution.
Data Reduction: Data reduction results in a reduced representation of the ...