Turn an application data migration initiative into a data governance pilot

Make application data migration into more than simply moving old data to a new system. It is also an ideal opportunity to showcase the potential value from a data governance program.

“Here’s the problem: you’re moving all the bad data from your legacy environment into your shiny new system. You must question which data should be allowed into the clean, new environment.”

—Rob Karel, vice president of product strategy at Informatica

As an essential part of any new enterprise application deployment or system upgrade, a data migration can accomplish so much more than simply transferring data. Use it as an opportunity to improve the quality of existing data and apply new, higher standards to the information powering your organization. It can also be an ideal pilot for a data governance program.

Data governance is an evolving discipline. It is aimed at giving organizations enterprise-wide control over the quality and security of their data by consistently applying standard processes and methods.

Governance programs should focus on:

  • Improving data quality
  • Protecting sensitive data
  • Encouraging information sharing
  • Providing business-critical data
  • Managing information throughout its lifecycle

"Here’s the problem with many data migration efforts: too often you move bad data from your legacy environment into your shiny new system," says Rob Karel, vice president of product strategy at Informatica. “Before you migrate data into a new application, you must question which data should be allowed into the clean, new environment.”

Karel suggests applying data cleansing rules, reconciling duplicates, and purging orphan and other unused data as a good first step toward data governance standards.

"Because support for data governance can be elusive, a helpful set of concrete steps is often needed to get the ball rolling," says Karel. He recommends using the following eight steps, as outlined by TDWI Research, to launch a data governance program with your next data migration:

  1. Learn data quality techniques and apply them. Data quality is a collection of techniques and practices that can contribute substantially to the success of your data migration efforts.
  2. Profile data early and often. Profiling data gives you a foundation for establishing standards for data quality, models, architecture, and usage rules for your new system.
  3. Build a business glossary as you go. A business glossary catalogs data and its characteristics. Define data from your legacy and new systems in terms of how the business will use it.
  4. Use data quality metrics. Use these metrics to continuously improve data, as well as to govern the lifecycle of the data pre- and post-migration.
  5. Remediate data that is out of compliance. Use enabling tools to allow data stewards to both automatically and manually mitigate data compliance issues at run time.
  6. Govern data in real time through validation and verification. Once your new system is up and running, monitor critical information on an ongoing basis to assure your data remains compliant with your data governance policies and standards.
  7. Use stewardship techniques to align data governance with business goals. Data stewards are critical because this role facilitates communication between business and technology teams.
  8. Collaborate as you govern. A cross-functional team should determine which data from the migration should be governed and how. Not all data is of equal importance.

Check out the complete TDWI Checklist Report to learn more about these steps.

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