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The best thing about using a table is that as you add or remove items from your list, your data validation list will update automatically.Note: The following examples use the Custom option where you write formulas to set your conditions.There are various measures of accuracy, but all measures of accuracy are dependent on the data that is used.

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This section introduces some basic concepts related to model quality, and describes the strategies for model validation that are provided in Microsoft Analysis Services.

For an overview of how model validation fits into the larger data mining process, see All of these methods are useful in data mining methodology and are used iteratively as you create, test, and refine models to answer a specific problem.

In computer science, data validation is the process of ensuring that a program operates on clean, correct and useful data.

It uses routines, often called "validation rules" "validation constraints" or "check routines", that check for correctness, meaningfulness, and security of data that are input to the system.

You can use data validation to restrict the type of data or the values that users enter into a cell.

One of the most common data validation uses is to create a drop-down list.

Therefore, data validation should start with business process definition and set of business rules within this process.

Rules can be collected through the requirements capture exercise.

Data validation rules can be defined and designed using any of various methodologies, and be deployed in any of various contexts.

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