![]() To this end, similar tutorials for other free-to-use software applications are springing up. Though their content is limited to languages and tools suited mostly for web developers, the value and quality of these sites are undeniable. Online resources like codecademy and w3schools offer a host of tutorials and assistance to those looking to develop their programming abilities and knowledge. With the advent of the exciting new hybrid field of Data Science, programming and data management skills are in greater demand than ever and have never been easier to attain. It reduces up to 90% of the time spent on the manual review of the PROC COMPARE output files. Number of variables in base and compared data sets are equal The SAS ® macro %threeN efficiently validates all the output files generated from PROC COMPARE in a short time and also expedites validation with accuracy. Number of observations in base and compared data sets are equal 3. Number of variables not in both compared and base data sets The status is flagged as Pass whenever the output file meets the following 3N criteria: 1. Number of observations not in both compared and base data sets 3. Data set name, label, and number of variables and observations 2. The proposed approach programmatically validates the output of PROC COMPARE in all the programs and generates an HTML output file with a Pass/Fail status flag for each output file with the following: 1. This is tedious, time-consuming, and error prone because there are more LST files to be reviewed and manual intervention is required. PROC COMPARE is one of the SAS ® procedures used to compare two data sets and confirm the accuracy In the current practice, whenever a program rerun happens, the programmer must manually review the output file to ensure an exact match. Of these, double programming is the most highly recommended and commonly used method to demonstrate a perfect match between production and validation output. Various validation methods are available to confirm data accuracy. In the clinical research world, data accuracy plays a significant role in delivering quality results. ![]()
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