Phase one of the data cleansing workflow with-in InfoSphere Quality Stage is to understand your organizational goals and requirements. It helps to
- Translate high-level mission directives into specific data cleansing assignments
- Make assumptions about the requirements and structure of the cleansed data
Data Quality needs & objectives varies in each organization. So before start designing data cleansing project need to understand the organizational goals that are driving the data-cleansing need and how they define data cleansing assignment (the effective goal). This insight helps gain a sense of the complexity of the intended cleansed data and provides a context which helps to make decisions throughout the workflow.
The success of a data cleansing project benefits from well-defined requirements for the output data results. As a best practice, provide opportunities throughout the every phase for domain experts and knowledge holders, who understand the organizational requirements of the data, to review the output results, to help iteratively refine requirements, and ultimately to approve the results. This collaborative process helps you meet the organizational requirements, increasing your chances for successful quality results.