📌 Intelligent Data Validation Summary
Intelligent data validation is the process of automatically checking and verifying data accuracy, completeness and consistency using advanced techniques such as machine learning or rule-based systems. It goes beyond simple checks by learning from patterns and detecting errors or anomalies that traditional methods might miss. This approach helps organisations catch mistakes earlier, reduce manual review, and ensure higher data quality.
🙋🏻♂️ Explain Intelligent Data Validation Simply
Think of intelligent data validation like a really smart spellchecker for data. Instead of just looking for obvious mistakes, it learns what correct data usually looks like and spots unusual or suspicious entries. It is like having a teacher who not only checks if your homework is done, but also notices if something looks strange or out of place, even if you did not make a clear mistake.
📅 How Can it be used?
Intelligent data validation can automatically detect and correct errors in customer data entered on an online registration form before it is saved.
🗺️ Real World Examples
A hospital uses intelligent data validation to check patient records as they are entered, automatically flagging unusual medication dosages or missing information so staff can fix issues before they cause problems.
An e-commerce company applies intelligent data validation to its product database, identifying duplicate listings, inconsistent pricing, or errors in product descriptions to maintain a reliable online catalogue.
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