Data Warehousing Questions
Data cleansing in data warehousing refers to the process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in the data stored in a data warehouse. It involves various techniques such as data validation, data transformation, and data enrichment to ensure that the data is accurate, complete, and reliable for analysis and decision-making purposes. Data cleansing helps improve data quality and integrity, enhances the effectiveness of data analysis, and ensures that the data warehouse provides trustworthy and valuable information to users.