The One Time Methodology

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This presentation will introduce a simple but powerful concept called the “One-Time Methodology” for encapsulating data in applications. Extensive SAS/AF® development experience is not required, though it will help to have had exposure to the basics of SAS/AF and SCL (SAS Component Language). The methodology can be applied in other application languages.

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The One Time Methodology

  1. 1. The One-Time Methodology: Encapsulating Application Data Mark Tabladillo, Ph.D. March 31, 2003
  2. 2. Introduction The YTSS (Youth Tobacco Surveillance System) started in 1998 y ) YTS = Youth Tobacco Survey GYTS = Global Youth Tobacco Survey Since 1998, over 1,000,000 surveys have b h been processed f 35 states and d for t t d 100 international sites
  3. 3. The Challenge 10 States (1998) to 30 States (1999) 2 000 to 3 000 manually audited base 2,000 3,000 SAS code YRBSS (Youth Risk Factor Behavioral Surveillance System) Model
  4. 4. Finding a Starting Point First SAS/AF Application Similar YRBSS SAS/AF Application New base SAS Code
  5. 5. The “One Time” Rule Where should information be once defined?? Short Info Long Info Non-Modifiable Enumerated Standardized Constants C t t SAS D t Datasets t Modifiable FRAME Customized Variables V i bl SAS D t Datasets t
  6. 6. Enumerated Constants Using a specific name, defined once, so that a variable is referenced Tip: Don’t assign values in declarations Example: Tab names for Tab Layout Preserves the “one-time” rule
  7. 7. Standardized SAS Datasets (Interchangeable with SCL lists) Example: State and Country Codes Preserves the “one-time” rule
  8. 8. Frame Variables Allow user to define value Provide error checking for data entry Example: Name of “Level” Preserves “one-time” rule P “ ti ” l
  9. 9. Customized SAS Datasets Large amounts of information, beyond a screen Microsoft Excel typically better than Access Example: Regional Layout Preserves the “ P th “one-time” rule ti ” l
  10. 10. Making the Application Work How to Access Datasets – use the datasets and SCL variables to submit code How to Check Data Integrity – check data as close to the source as possible
  11. 11. Making the Application Work How to Prepare to Submit – check combinations before running a p g process How to Monitor Processes – Save the output and log files, and track overall files process in a log dataset
  12. 12. Generalized Lessons… Understand the user objectives in terms of both functionality and also in terms of deliverables. Start with what works (encapsulate success). As the application changes, continually apply the “one-time methodology”. Standardize all data possible.
  13. 13. (more) Generalized Lessons Allow users to modify brief information on screen, and complex information within datasets. Expect the application to monitor data integrity as well as processing efficiencies. Use the methodology outside of SAS/AF.

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