Data reconciliation (DR) is a term used to describe a verification phase during a data migration where the target data is compared against the original source data to ensure that the migration architecture has transferred the data accurately without errors.

It is an extremely important part of any migration process. During a data migration, it is possible for mistakes to be made along the mapping and transformation logic.These problems can lead to various issues such as:

Missing records

Incorrect values

Missing values

Badly formatted values

Duplicated records

Without the data reconciliation stage, these issues can go unnoticed and severely damage the overall accuracy of your data leading to inaccurate insights and not to mention the customer dissatisfaction. Also, if these issues are not identified immediately as a result of lack of proper reconciliation, not only will an organization's reputation be at risk but also resolving these errors later on in the process will not be cheap in terms of cost or time and might cause significant delays. In short- The impact will be significant ! 

https://www.linkedin.com/pulse/importance-data-reconciliation-quality-migration-niharika-singh/