ataFlux software and SAS data sets support different data types. Accordingly, automatic data-type conversions will take place when Data Management Studio software reads or writes SAS data sets. Also, nulls and missing values will be converted to other values. These changes can impact features that depend on particular data types. For example, when a profile reads a SAS data set, SAS fields with a format that applies to datetime values will be reported as datetime. SAS fields with a format that applies to time values will be reported as a time and SAS fields with a format that applies to date values will be reported as a date. As a result, the profile will not calculate some metrics such as Blank Count or Maximum Length for those fields. The following data-type conversions are made automatically when DataFlux software, such as a data job or a profile, reads SAS data. For jobs: SAS numeric columns with a format that applies to date, time or datetime values will be converted to a DataFlux field of type date. For profiles: SAS fields with a format that applies to datetime values will be reported as datetime. SAS fields with a format that applies to time values will be reported as a time and SAS fields with a format that applies to date values will be reported as a date. Other SAS numeric columns will be converted to a DataFlux field of type real. SAS character columns will be converted to a DataFlux field of type string with the same length as the SAS character column. Nulls and missing values will be converted to other values, as follows. SAS missing values will be converted to DataFlux null values. SAS special numeric missing values, whether they are specified with the MISSING statement in a SAS DATA step or with a dot followed by a letter or underscore, are also converted to null values. DataFlux null values will be converted to SAS missing values. A DataFlux field of type string that contains a blank will be converted to a SAS character field containing a blank. This blank will be interpreted by SAS as a missing value. Regards, Rachel Gomez
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