DM08
Mrs. Clean Tackles Dirty Data
Invited
Janet E. Stuelpner
Citigroup
Abstract:
What is clean data and how do you clean it? This is an age-old question that has some pretty easy answers. There are some techniques that can be used to find invalid data values in both numeric and character data, missing values of any type and duplicate o
bservations. Simple procedures and DATA steps can be used to ferret out inappropriate observations. This paper will illustrate some of the techniques used after data entry is complete and the data has to be reviewed and cleansed.
Biography:
Janet Stuelpner provides training and programming support in the areas of clinical trials, outcomes research and the financial industry. Janet has several degrees in the sciences. She has been a SAS user for over 21 years on many different platforms. Origi
nally a systems programmer, she has now turned her focus to teaching DB2 SQL and SAS. She is a section chair at NESUG, a member of the HASUG steering committee and has been a presenter at users groups at all levels.