Data Cleaning and Transformation focuses on preparing raw data for analysis by removing inconsistencies and converting it into a structured, usable format. It enables organizations to improve data quality and ensure accurate insights for decision-making. This training explains techniques for handling missing values, duplicates, outliers, and inconsistent formats. It also covers data transformation methods such as normalization, aggregation, encoding, and feature engineering. You will learn how businesses use cleaning and transformation processes to build reliable datasets for analytics and machine learning. The course also highlights best practices for creating efficient and reusable data preparation workflows.
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