Symbiotic Cycles of Adding Value to Information
TDWI 2006 poster:
Data profiling, data integration, and data quality are three key data management practices that go together. After all, they address related issues in data assessment, acquisition, and improvement. For example, data integration projects ferret out quality issues. Likewise, data quality projects depend on integration technologies to access and enhance corporate data. Data profiling—though sometimes neglected—is required as a planning task when designing data quality and data integration projects, as well as a recurring task that tracks data improvement over time. And the three practices are inherently related through a common goal, namely: to add value to information continuously.
The symbiotic cycle illustrated in this TDWI poster reveals some of the relationships among data profiling, integration, and quality. It also shows how associated tasks recur over time—in a more or less consistent order—although some repetitions of the cycle may skip some steps. Every organization’s solution will differ, but this model can be a starting point for data management professionals hoping to integrate the three practices of data profiling, integration, and quality.