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- W2741256381 abstract "When faced with a difficult data analysis problem, a SAS® programmer has many options to solve the problem. In this paper, three different approaches are evaluated and compared in terms of effectiveness, efficiency, debugging, and clarity of the code. The three methods include linearizing the data, using SQL Cartesian joins, and using sequential data processing. Inconsistencies in the raw data caused the data linearization to be problematic. The output generated by a multi-stage, air monitoring instrument that collected several measurements every 5 minutes for 9 years resulted in more than 800,000 records. The large number of records and the need for many-to-many merges resulted in a long run time for the SQL code. The sequential data processing, although older technology, provided the most time efficient and error-free results." @default.
- W2741256381 created "2017-08-08" @default.
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- W2741256381 date "2015-01-01" @default.
- W2741256381 modified "2023-09-23" @default.
- W2741256381 title "Examination of Three SAS® Tools for Solving a Complicated Data Summary Problem" @default.
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- W2741256381 hasPublicationYear "2015" @default.
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