Data Cleansing

The process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database.

What is Data Cleansing?

Data cleansing is the process of identifying and rectifying errors, inconsistencies, and inaccuracies within a dataset to ensure its quality and reliability. This involves detecting and correcting typos, missing values, duplicate entries, and formatting issues that may distort the integrity of the data. By cleansing data, organizations can enhance the overall quality of their information, leading to more accurate analyses, improved decision-making, and increased operational efficiency. It involves using various techniques such as data profiling, validation rules, and deduplication methods to clean and standardize the data for optimal use. Data cleansing plays a crucial role in maintaining data integrity and consistency, ultimately maximizing the value and usability of the information within an organization.