Kimball University: Eight Recommendations for International Data Quality

Language, culture, and country-by-country compliance and privacy requirements are just a few of the tough data quality problems global organizations must solve. Start by addressing data accuracy at the source and adopting an MDM strategy, then follow these six other best-practice approaches.
5. Use at the time of data capture to determine the actual time of day of every transaction that occurs in a remote foreign location. Store both universal time stamps and local time stamps with every transaction.

6. Choose a single universal currency (dollars, pounds, euros, etc.) and store both the local value of a financial transaction together with the universal currency value in every low-level financial transaction record.

7. Don't translate dimensions in your data warehouse. Settle on a single, master language for dimensional content to drive querying, reporting and sorting. Translate final rendered reports, if desired, in place. For hand-held device reporting, be aware that most non-English translations result in longer text than English.

8. Don't even think about establishing privacy and compliance best practices. That is a job for your legal and financial executives, not for IT. You do have a CPO and a CCO (Privacy and Compliance, respectively), don't you?

For more information, please consult these additional references, which detail the approaches I use for addressing international data quality. The best reference for understanding international data representation issues is Merriam-Webster's Guide to International Business Communications, Second Edition, by Toby Atkinson. I have written two relevant white papers: Architecture for Data Quality in an Enterprise DW/BI System and Architecture for Integration in an Enterprise DW/BI System. These white papers are sponsored by Informatica but are free from vendor product recommendations.