What is the purpose of data cleaning in data enhancement?

The purpose of data cleaning in data enhancement is fundamentally about improving the quality of the dataset by identifying and fixing errors or inconsistencies within the data. This process is essential because high-quality, reliable data is critical for accurate analysis and decision-making. Data cleaning ensures that inaccuracies such as duplicates, missing values, and incorrect formatting are addressed, thereby enhancing the integrity and usability of the dataset.

Improving dataset quality enables analysts to derive more accurate insights and make informed decisions based on the data. By concentrating on rectifying issues within the dataset, data cleaning helps to build a solid foundation for subsequent data processing and analysis tasks.