In this complete act, there are many chances of facing potential risks by the teams. And, to validate this procedure, there is an effective need for substituting testing and this is nothing but, Data Migration Testing. Data Migration Testing works as a verification method for the data migration process and helps to limit the downtime, issues related to data integrity, etc. But, to make this process assured with the quality, there are many data migration testing challenges to overcome.
In the present era, data is having very crucial importance in building the success blocks for enterprises. Enterprises need to take every safety measure to secure data in every procedure, especially during data migration. Yes, in the method of transferring data from one legacy system to another targeted system, it is important to validate if the data is transferred with the same quality, without any data loss, etc.
Data Migration Testing is the methodology that is helping the teams to validate the process of data migration. However, to ensure that the transferred data is quality assured, data migration testing requires to overcome several challenges.
What is Data Migration Testing?
Data Migration Testing is the methodology to validate the process data migration. The data migration testing strategy ensures that the data transferred to the target system is meeting the quality standards, functions the same as the old structure, etc.
It is the most challenging activity for many enterprises as it includes a high level of risk. While performing this testing strategy there will be many challenges to overcome.
3 Important Data Migration Testing Challenges
Data Loss: This can occur when the data from the legacy system is transferred to the targeted system. Generally, data have mandatory and non-mandatory fields. If the data is lost from the non-mandatory fields, then this may not be a huge data loss as it can be updated. But, if the data is lost from the mandatory fields, then this can be a failure as huge data can be lost. These scenarios can be resolved by retrieving data from backup or audit logs.
Mismatch in Data: After transferring the data from the legacy system to the new one, this data mismatch challenge can occur in the new system. Usually, these occur as a result of the change in data type, change in the storage format, etc. To mitigate these mismatches, it is necessary to do the required modifications to correct or accept the mismatched data.
Data Quality: This challenge occurs when the data transferred to the targeted system perform with poor quality. These can be due to many factors such as poor data analysis, if the data in the legacy system is invalid, etc. These can result in unsuccessful productivity, increase operational costs, data integration risks, etc. To overcome these, it becomes important to improve business standards.
Conclusion:
Data Migration is a sensitive process of transferring data from a legacy system to a new or upgraded system. This is an essential process for many enterprises to enhance their business standards, but this can also be a failure if these data migration methods are not tested with Data Migration testing practices. Leverage, data migration testing services from next-gen independent software testing service provider.
