Applying Data Status and the Danger of Overloading

Everyone wants valid data, but does everyone agree to what valid means? When consolidating different data sources into an enterprise applicable system of record, it is critical to understand the source data so proper data status can be applied. Distinct data status application provides a flexible datasets for consumers, where overloaded data status application leads to a constricted data difficult to consume.

In this session, the audience will see:

Real examples of data status overloading, the repercussions, and how they were corrected
How to identify and avoid status overloading before implementation

When Lisa Cutler-Farwig started with Schlumberger more than eighteen years ago as an offshore geophysicist, the last thing she thought she would be involved with was the Master Data Program. However, over the years, her role in the company evolved. She moved into a business segment's headquarters to support Personnel and Marketing functions at a time when an enterprise wide business intelligence (BI) tool was being implemented. This was the driver to develop and implement global business processes to capture data correctly. However, she found even when the data was captured correctly, cross-functional reporting proved difficult due to the lack of a common language across the various enterprise systems. So, when the opportunity to join the master data team arose, she jumped at the chance. For the last three years, she has managed projects to bring enterprise data together.