Sql validating populated columns

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They can be used very effectively where the attributes are sparse for any given entity and very numerous across all entities. Sparse columns and column sets can be used in conjunction, and are ideal for fields that contain mostly NULL values.

Sparse columns handle NULL values extremely efficiently; column sets combine all sparse columns into an XML representation as a new column.

Sparse columns are ordinary columns, with the addition of the SPARSE property.

To create a table with sparse columns, simply use the SPARSE keyword: This can also be accomplished by changing the ‘Is Sparse‘ column property to ‘Yes‘ in table design view in the SQL Server Management Studio GUI: A sparse column must be NULLABLE, so the NULL keyword is optional.

The XML field accepts inserts, and its data can be extracted and modified easily.Given that trade-off, Microsoft recommends not using sparse columns unless the percentage of NULL values in a column is high enough that a 20 percent to 40 percent storage savings gain would result.The ratio of NULLs to real values that would warrant implementing a sparse column differs for each data type. Then its leap years based on 100 year and 400 year boundaries... yes this can be one of the solution but the update query will look so messed up . I was thinking something like using case statement in update and check for converting date using to_date and handle exception in the case block . I know function will make the thing a lot easier but I need to try all the other options before going for a function lets hope something like this works :-D this is my first question ever . Then you could check the month/day mappings individually..now you've got leap years to look out.

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