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This example shows a business process Total Quality Management diagram that can be then analyzed for ways to improve the process effectiveness and diagnose quality issues that require resolution. As mentioned in my post describing the major business processes that comprise a data governance function, the Define processes documents data definitions and business context associated with business terminology, taxonomies, relationships, as well as the policies, rules, standards, processes, and measurement strategy that must be defined to operationalize data governance efforts. Ensures everyone is on the same page –data architects, modelers, developers, stewards and data consumers: business process owners as well as operational and strategic decision-makers. Common, standardized reference data ensures the ability to reconcile, aggregate and gain insight from data shared across disparate application, functional, geographic or organizational silos or across B2B trading partners.
When operationally implemented in the Apply process stage, business rules are the key to ensuring data is trusted, secure, and ultimately fit for business usage. When defined, approved, evangelized and enforced appropriately, these policies have the power to evolve your corporate culture to one that manages data as an asset.  Without these top-down, executive-driven policy mandates, it will be difficult to change past behavior impacting data quality and security.

When a data governance effort is ready to scope and define what policies it must document and implement, it can start with the work that’s already been done and reconcile which policies should be owned by the data governance effort, which should simply be recognized and complied with, and which should be replaced or improved.
Data governance efforts will not receive sponsorship, resources, funding or prioritization without a means to measure the value and effectiveness of the efforts. Neither the service provider nor the domain owner maintain any relationship with the advertisers. TQM diagram helps to show clearly step-by-step process and to compare the ideal and real process stages visually. Process of defining data relationships, mappings and hierarchies at both the metadata (data modeling) and data (business hierarchies) levels. The process of creating and documenting logical business requirements to build the rules and policies for data validation, cleansing, enrichment, matching, merging, masking, archiving, standardization, etc.

Process of defining data governance-driven policies such as data accountability and ownership, organizational roles and responsibilities, data capture and validation standards, data access and usage, as well as data masking, archiving, subsetting and retention. It’s likely other efforts within an organization already document business- or IT-driven policies that set parameters on how enterprise data should be managed and used, but may not currently label it a “data governance” policy.  These include policies for information security, data privacy, GRC, IT governance and others.
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business process management definition wikipedia

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