Hey Erin,
This definitely sounds like a very challenging project to start. Not sure what level of data maturity and governance your organization has but I would start with securing true data basics and not to ignore obvious elements analysis (e.g. zip code, country code & their proper mapping across systems for Customers / Vendors etc.).
I would say the mapping of data, its criticality and R&R would be the key. So very high level this would be my plan to even start planning this approach:
- Define the entities that need to be overseen: List their basic data & criticality of the data
- Define Governance: data owners & approvers on any cleansing activity
- Set rules of cleansing & alerts for quality issues with the data governance team/ data owners. Check where the data rules are fully automatic vs. need human intervention.
- Define who is providing the quality analysis & performing cleansing. (outsourced vs. internal team main responsibilities)
- Define downstream dependencies & communication map in case of cleansing activities or regular data reviews
- Set frequency of reviews
- * Quite obvious but: set success criteria / benefit tracking for every entity subject to data quality checks.
Hope this was somehow helpful, if not looking forward to more contributions form the community members.
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Maria Glosnicka
GEHC
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