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.