In most relational RDBMSs, nulls represent the absence of data; that is, RDBMS nulls do not sort or compare because there is no data on which to operate. However in SAS, we have the concept of a missing value, which is quite different. A SAS missing value is a special, reserved floating point number that can have 28 possible values represented by the following elements:

• A period ( . )
• An underscore and a period ( _. )
• A period and an alpha ( .A through .Z ).

Missing values make a lot of sense for SAS procedures that utilize data where more than one missing value is needed such as survey data that might need to represent missing values as .D for “do not know” and .R for “refuse to answer” for example.This ability to evaluate missing values with standard comparison operators has significant implications when passing queries to an RDBMS for processing because the RDBMS interprets nulls differently than SAS.

For a detailed discussion of these differences, see the technical paper Potential Result Set Differences between Relational DBMSs and the SAS System.

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