What is data validation in analytics?
An example of an AI chatbot conversation about data validation in analytics.
What is data validation in analytics?
Data validation in analytics refers to the process of ensuring that data is accurate, complete, and reliable before it's analyzed.
Why is data validation important?
It's crucial because it helps prevent errors in analysis, leading to more reliable insights and better decision-making.
What are some common methods of data validation?
Common methods include range checks, format checks, consistency checks, and cross-validation with other data sources.
Can you give an example of a data validation rule?
Sure! A simple rule could be ensuring that a date field only contains valid dates, rejecting any non-date entries.
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