1. A method for checking the accuracy and quality of your data, typically performed prior to importing and processing. It can also be considered a form of data cleansing.
2. It ensures that your data is complete (no blank or null values), unique (contains distinct values that are not duplicated), and the range of values is consistent with what you expect.
3. Often, data validation is used as a part of processes such as ETL (Extract, Transform, and Load) where you move data from a source database to a target data warehouse so that you can join it with other data for analysis. Data validation helps ensure that when you perform analysis, your results are accurate.