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SQL Server represents missing data values with NULL values, but SAS has a minimum of two ways of representing missing values: a period (.) for numeric missing values and a blank space (' ') for character missing values. Even the topic of representing and processing missing data values is substantially different between SQL Server and SAS. Double precision floating point numbersīecause SQL Server data typing is much richer than SAS, translating SQL Server values for use with SAS can be challenging.Characters up to a 32,767 character maximum.Natively, SAS supports just two data types: Interoperability between SQL Server and SAS is complicated especially by incompatible data types. Some Background Thoughts about the Solution This installment in the series closes with some ways of enriching the solution and resources for learning more about SAS. csv file with data values that are ready for transfer to SAS. Tip support materials include a script for creating a table and populating it with values for export from SQL Server to SAS as well as a. This first installment takes you from a SQL Server staging table for SAS through to its transfer to a SAS data set. In this first installment, you get a hands-on feel for the topic starting with coverage of the reasons and steps for creating a staging table in SQL Server for transfer to SAS. This tip is the first in a two-part series on presenting a simple set of techniques to handle interoperability between SQL Server and SAS with minimum hassle.
#Sas version 9 data sets software#
Since SQL Server and SAS are from different software vendors, newcomers to the task may find interoperability challenging.
#Sas version 9 data sets professional#
Therefore, if data you manage as a SQL Server professional has analytical applications in these or other areas, you may very well find yourself preparing data for SAS analytics professionals or even running SQL Server data through a SAS analytics package without support from SAS professionals. SAS is a popular tool in such areas as healthcare and retail analytics.