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Table Of Contents
Mastering SAS Programming for Data Warehousing
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This chapter described many strategies and considerations to be made when developing code to read big data into SAS. SAS native data file formats *.SAS7bdat and XPT contain metadata that makes reading them into SAS easy and accurate. However, the downside is that these datasets can take up a lot of storage space.
LIBNAME statements in SAS point to external locations for reading and storing data. Using LIBNAME statements, the SAS user can convert *.csv and *.txt files to *.SAS7bdat datasets for storage, and can also convert them to XPT. While storing data in *.csv and *.txt format can conserve space, the downside is that oftentimes specialized infile code is necessary for reading this data in so that it is properly formatted in SAS. While the automation involved in PROC IMPORT can help with this, when regularly transferring large raw data files, usually, long and detailed infile code must ultimately be developed and maintained.
Because of SAS's ability to handle...