Once we’ve profiled our data, as we discussed in the previous tutorial, we can now look at how we will deal with data quality issues. Ultimately, this results in the rejection of data if it does not meet our quality criteria.
Within our data quality Jobs, we are not attempting to correct data, we are simply rejecting the data if it does not meet our quality criteria. If we want to make corrections to the data, then we will achieve this during other phases of our migration logic, for example, Data Preparation.
As with most aspects of our data migration, quality control is not a linear process. We may apply quality checks at different points of the migration, as we build-up our finalised data, for loading in to Salesforce.