With respect to data quality, many factors come into play. Raw data from claims or from an EMR database are not suitable for analysis. Turning raw data into usable information requires preparation, including normali-zation and validation. Only then can an organization gain trustworthy insights from the information and put it to use in maximizing patient care, reducing risk and strengthening a business’s bottom line. While the concept of data quality is widely accepted, most health care organizations define “good data” in different ways. One common thread, however, is the overwhelming need to gather and analyze information from one end of the spectrum to the other.