Once Data is Standardized and matched final stage in data cleansing workflow is to evaluate
the results of the previous phases and to identify any organizational
process improvements. The success of a cleansing project comes from
iterative reviews and refinements throughout each phase.
In this phase of the workflow need to look at the results of the process
and determine whether need to perform any of these activities:
- Revisit a previous phase
- Refine some of the conditions
- Repeat the process, starting from the phase you revisit
If data quality goals are simple results produced post data cleansing iteration might be satisfactory. If it is not so need
to repeat this workflow, making different decisions and further refinements
with each iteration. Although it is the final step of the data
cleansing process, for a well-designed and developed job or a sequence
of jobs this requires to evaluate each step followed and decides future actions. As
a best practice results should be evaluated at the end of each phase to avoid following entirely wrong direction with inconstant data. This process fine tunes a job and its stage components
to achieve the highest quality data.
At the end of the design and development of data cleansing jobs should
evaluate the entire process. It means insight about data, data cleansing process, data collection process and evaluation process. Evaluation helps to make changes to next
data cleansing project and refine jobs or help organization
make changes to its business rules or even to its organizational goals.Evaluating the results of data cleansing process can help organization maintain data management and ensure that corporate data
supports the organizational goals.