The Nine Major Risks to Your Data Migration Project

Posted by Utopia Marketing on July 31, 2012

DATA_MIGRATION_RISKS.jpgData migration is a complex process. In-and-of itself, it can be logically done. What it’s basically about is a thousand discrete steps that you need to do in order. If you get those steps out of order, then the entire project could be in jeopardy. One of the key components of doing a data migration is what we call “the pick and shovel work of doing the business rules development” and making sure you capture those.

If you’ve conducted a data migration, or you’re about to do one, you can expect—at somewhere, some point in that project—to hear one of these nine different statements.

  1. “Profile the data? Why? It’s just going to slow us down.”
  2. “We’ll rely on the legacy systems data quality; IT cleansed it.”
  3. “Everyone knows the business rules; we don’t need to redefine them.”
  4. “Define the target-system purpose? Why? We already know what that is; we just need to upgrade or migrate the application.”
  5. “Data governance? Everyone works on it; it’s gotten us this far. Works just fine.” “Do that in extra coding?”
  6. “That function’s built into the ETL tool. It’s automatic.”
  7. “The business subject matter experts are too busy to work with us on this, on building out the business rules. IT will represent them.”
  8. “Data validation—we can do that at the end. We have the time.”
  9. “We can test with a subset of the data. We don’t need to load all the data until the very end.”
At Utopia, what we’re after is offering you the tools to mitigate the risks that these nine statements are kind of alluding to. If you don’t mitigate these risks, you’re going to be sub-optimizing your delivered system. You’re going to have a failed deployment, certainly cost-overrides, and maybe schedule overrides.

Learn more about how Utopia's team of data experts utilize Enterprise Data Lifecycle Management™ (EDLM™), a proven framework and methodology, during a data migration rollout.

Topics: Data Quality, data migration, EDLM