4 Common Data Migration Mistakes - And How to Avoid Them

While creating a data migration plan can be a daunting prospect, our customers are seeing the many benefits of transferring data from their legacy systems to more modern infrastructures. By keeping in mind the strategies for avoiding mistakes, you’ll set your systems and teams up for success and enable your data migration to positively impact your business.

Data migration mistakes and how to avoid them

With the enterprise embracing digital business, infrastructure and operations leaders are being asked to build agile infrastructure and processes that support rapid and evolving enterprise needs. With data volume and variety expanding rapidly, effectively migrating that data is essential to digital transformation. These days it’s also a big business, with the global market for data migration projected to reach $22.8 billion by 2026.

Cloud migration is frequently mentioned in the press, but there are other kinds of data migration as well. Application migration involves transferring application programs or systems to the cloud or between clouds. Storage migration is the process of transferring data to a modern platform from outdated arrays, optimizing performance and scaling efficiently. Business process migration replaces and upgrades business management tools and migrates data from one database or application to another.

At Teradata, we’ve helped thousands of customers in various industries execute all kinds of data migrations. Over the decades, we’ve honed our approach, anticipating challenges, avoiding downtime, and expediting the entire process. Through these experiences, we’ve identified four common mistakes that can derail a data migration plan and how to avoid them.

Data Migration Mistake #1: Not involving business users from the start

The IT team may be accountable for data integrity after a migration, but business units are the data’s ultimate end users. By not keeping them informed and listening to their feedback about merging, cleansing, or restructuring the data they work with every day, business users may use data incorrectly or flood IT with support requests after the migration occurs.

A thorough assessment of your current environment informs the important decisions you’ll need to make about the process, such as when and where to involve stakeholders. Having a deep understanding of your infrastructure, the data you need to migrate, the order in which to do it, and compatibility issues will give you a better idea of the project scope.

Data Migration Mistake #2: Not preparing your source data

At the beginning of your process, define what source data you’ll be moving and then examine it thoroughly. Duplicates, gaps, misspellings, and errors in your data could result in critical failures as you try to configure your data to fit new parameters. You need to thoroughly cleanse your source data and identify any ways you may need to transition it into new criteria or categories.

Migrating your data is a great opportunity to remove any legacy structures that no longer work for your users and remove inefficiencies. But be sure to cleanse your data before the migration process, not in the middle of it.

Data Migration Mistake #3: Not establishing sustainable governance

In the midst of managing infrastructure and load-related issues, defining the governance structure of your data can be a rushed or forgotten step in a migration. But understanding who owns what data and who can access, edit, or remove it is critical.

You may also need to verify that your organization has a process in place for managing the lifecycle of data in the first place. And your enterprise’s business and validation rules may not be current, or your data may not be in compliance with these rules. Instead of inheriting all of these inconsistencies, take the time now to address these issues so you don’t migrate your enterprise’s problems as well as its data.

Data Migration Mistake #4: Not testing and validating

It’s not realistic to expect that you won’t encounter issues during your migration. Like in any other IT project, testing should be a critical-path activity throughout the process, not just at the end. Define who will test and evaluate data as well as sign off on the tests’ results.

You can conduct your testing in development environments to minimize downtime, a strategy Teradata’s Consulting team often takes when migrating our enterprise customers’ data.

Once the migration is complete, keep testing. Schedule follow-up meetings with your stakeholders to discuss issues, lessons learned and action plans going forward.

While creating a data migration plan can be a daunting prospect, our customers are seeing the many benefits of transferring data from their legacy systems to more modern infrastructures. By keeping in mind the strategies for avoiding the four mistakes above, you’ll set your systems and teams up for success and enable your data migration to positively impact your business.

And you don’t have to migrate your data on your own. Whether you’re a Teradata customer interested in upgrading to Vantage or haven’t worked with us before, please don’t hesitate to contact us today to learn more.