Data Transformation

Data transformation is the process of converting data from one format, structure, or type to another to make it more suitable for analysis, visualization, or machine learning. This process involves cleaning, filtering, aggregating, merging, and reshaping data to create a consistent and meaningful representation of the underlying information. Data transformation is a critical step in the data pipeline as it helps to improve data quality, reduce redundancy, and enhance data usability. It is often performed using tools such as ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes, which automate the data transformation process and enable data scientists and analysts to work with clean and structured data.
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