Data Validation

#Terms

WHAT IS… ?

When data is used to train a new model, it is important to ensure that the data is valid. Data validation means checking the quality of source data before using it for training models. It ensures that anomalies that are infrequent or manifested in incremental data are not silently ignored. It focuses on checking that the statistics of the new data are as expected (e.g. type of statistical distribution and its parameters)

HOW IS IT USED ?

Data Validation is done in order to ensure that data-based systems are working as expected.