Data Transformation

Simple Definition for Beginners:

Data transformation is the process of converting data from its original format into a format that is suitable for analysis, reporting, or other purposes.

Common Use Example:

A company performs data transformation on raw sales data, cleaning and formatting it to generate monthly sales reports for management review.

Technical Definition for Professionals:

Data transformation involves modifying, reformatting, or restructuring data to prepare it for analysis, visualization, or storage. This process includes tasks such as cleaning data (removing errors, duplicates, or inconsistencies), filtering and sorting data, aggregating data (e.g., summing values, calculating averages), merging or joining datasets, and applying transformations (e.g., normalization, standardization). Data transformation is often part of the broader data processing pipeline, which includes data extraction, transformation, and loading (ETL) processes. It is essential for ensuring data quality, accuracy, and compatibility with analytical tools and systems.