Avoiding Common Pitfalls in Data Migration

There are many potential pitfalls that organizations need to avoid in order to ensure a successful migration. Here are some common ones to watch out for during data migration: 

• Lack of planning and management: Poor planning and management can lead to delays, and project failure. Some migration plans are so ambitious that they are broken by design. In other cases, a lack of organization means that previous activities like customization are delayed while the go-live deadline remains unchanged and the data migration runs into an unresolvable time crunch. Inadequate planning can also result in compliance issues and data security risks. To avoid this, organizations should invest sufficient time and resources in planning and managing the migration. This includes setting clear goals, migration prerequisites, defining timelines, and identifying potential issues and risks. It is a small price to be paid upfront in order to save a lot of pain and cost later in the project.

• Building migration tools and scripts on the fly: It is not uncommon for certain types of teams to use makeshift or inadequate tools and techniques that have not been proven for the task at hand or require a lot of error-prone manual labor. There is a high risk of the migration team losing track over a multitude of script and file versions they are juggling, potentially even across several local installations. This can result in data corruption, leakage, loss, and inconsistency. Project delays and increased costs are among the lesser of the evils that may result from that. To mitigate such risks, organizations can use reliable and proven migration tools and techniques. This includes using dedicated tooling for migration automation and management, performing data profiling and analysis, and validating data quality.

• Failing to test the migration before going live: When a data migration project is performed without test runs, this can lead to terrible surprises in the new application. For one thing, not all records may be accepted by the production instance. In the event of complications, delays are very likely. Even worse, however, are data records that make it into the production instance but are mixed up or accessible to user groups that should not actually have access to them. Furthermore, it may lead to frustration and decreased productivity when users don’t find the data they expect and need in the new application. Therefore, before letting data loose on actual users, organizations should perform comprehensive testing of the migration before going live. This includes testing data integrity, data quality, access rights, and system performance.

• Poor communication with stakeholders: Poor communication with stakeholders can result in misunderstandings, lack of support, and delays in the migration process. It is important to keep in mind that most stakeholders have a full-time job besides the migration project they are supposed to contribute to. To avoid such issues, the migration team should state the required bandwidth and response times clearly, plan ample turn-around time for responses, state the requests in language that can also be understood by a business user, and make sure to communicate regularly and transparently with all stakeholders in their period of involvement in the migration process. This includes defining clear roles and responsibilities, setting up regular meetings, and providing easy-to-digest migration education to all stakeholders.

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