The focus of this month’s newsletter is on software tools for evaluating data quality and modifying or correcting data to address deficiencies in quality. Researchers and analysts often seek to implement program code that can be used to routinely and systematically produce measures of data completeness, correctness, and timeliness. Access to data quality macros or subroutines means that reports can be consistently generated with just a few keystrokes. Routine data quality evaluations are important for ensuring that data quality does not erode over time, and they can be the basis for ongoing dialogues between data providers and data users.  Specialized software tools to measure and address specific data quality issues, such as missing data, are equally important to include in the analysts’ toolkit.  
 
At the 2013 SAS®Global Forum in San Francisco, there were a number of presentations on software tools for data quality, two of which were made by analysts working with Canada’s administrative health data. I have provided links to these technical papers in the Links of Interest. As well, I recently came across an interesting website that highlights a recent SAS® book entitled “Data Quality for Analytics” that you may find useful. 
 

Lisa Lix
 

Links of Interest