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Running a Robust Data Management Plan
Karen Beckmann, Senior Director, Information Technology, Rocky Mountaineer


Karen Beckmann, Senior Director, Information Technology, Rocky Mountaineer
3. Extract, agree, and publish formulas and business rules that have been built into reports; capture this in your business glossary.
4. For critical data fields, identify source systems and accompanying changes (data lineage), and capture all of these in your data catalog.
5. Work with your data advocate and data owner (preferably who creates the data) to define data quality standards.
6. Profile that data against standards to understand where corrections are required.
7. Work with source system owners (IT and business) to understand if source systems configuration (drop-down values and/or mandatory fields) and business processes can be changed to produce data to quality standards.
8. Run a script to complete a one-time data correction (ensure that you conduct a regressiontest of the impact of this data change before you move to production).
9. Run the clean-up script regularly until source controls are achieved and educate users on why they may temporarily see different results in the source versus your reports.
10. Publish quality reports through data profiles regularly (monthly) for the data owner and ensure they are incentivized to maintain quality.
Always remember the importance of delivering tangible business value. Do this through a robust change management and communications plan. Data management is not just about cleaning up data, but about changing the culture of your company. Your data consumers will indicate the impact clean data has on their confidence and trust. In addition, create a report and data certification process that gives others their confidence and trust in data. Articulating which gold-standard, trustworthy empowers data use.
Once your culture is changed and data is clean, you will discover what the industry means when they say, “data is the new oil”.
Data management is not just about cleaning up data, but about changing the culture of your company. Your data consumers will indicate the impact clean data has on their confidence and trust.
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