Data Quality (DQ) Tips is an OCDQ regular segment. Each DQ-Tip is a clear and concise data quality pearl of wisdom.
“Data quality is primarily about context not accuracy.
Accuracy is part of the equation, but only a very small portion.”
This DQ-Tip is from Rick Sherman's recent blog post summarizing the TDWI Boston Chapter Meeting at MIT.
I define data using the Dragnet definition – it is “just the facts” collected as an abstract description of the real-world entities that the enterprise does business with (e.g. customers, vendors, suppliers). A common definition for data quality is fitness for the purpose of use, the common challenge is that data has multiple uses – each with its own fitness requirements. Viewing each intended use as the information that is derived from data, I define information as data in use or data in action.
Alternatively, information can be defined as data in context.
Quality, as Sherman explains, “is in the eyes of the beholder, i.e. the business context.”