Enterprise Data Architecture – Quality Principles
1. A Single Architecture Framework and Standard Form of Each Object Define All Purposes of Data In A Single Architecture.
· This is a relatively small set; typically 20 or less
· The guidance is one standard object form, designed for one frame
2. Business Context Data will be Engineered and Formalized as an Enterprise Standard, at least two levels of sets.
3. All Enterprise Capability Has Core Dependency on Enterprise Data Quality and Data Governance.
· Enterprise Standard Form, Enterprise Fit, Standard Function/Purpose
· Meta-Models and multi-dimensional standards for Objects, Elements, Relationships and Semantics
4. Operational Data Stores will be 100% integrated and aligned based on master data.
5. The Conceptual Object Definition and the Physical Object Definition are one to one.
· Each frame conceptual object form is the basis for one physical object form
· A holistic definition for the enterprise standard requires a sufficiently high and broad perspective (enterprise, not a project).
· Supports reuse by semantically different but purposefully same objects
6. Physical Business data will be architected in its whole and final form; one framework object, one form.
· One type of object, one data store to manage and maintain
· Data does not flow, it has life cycle transitions and remains in one place until archival
· Replication should be avoided, unless in final state
· One fact in one form for any access or use, in any process or solution
· One set of common data access services for a framework object and reuse of those services
· One set of common data quality services for a framework object and reuse of those services
7. All Enterprise Business Data will be Designed Prior To and Independent of Use By Any One Application
· Application use and reuse is enterprise wide
· No variant forms and additional maintenance are allowed
8. A Data Purpose Dictionary Will Accompany Each Enterprise Standard Object Form
· Enterprise Data Purpose Dictionary is an enterprise data architecture product
· Governance requires definition standards: Definition, Purpose, Usage Examples & Description, Definition Standard
9. Operational Data Will be Maintained Through a Standard Functions Composed of Data Quality Services with Governance by Active, Context Dependent Data Quality Rules.
· Any application that creates or updates data will pass a message to the data quality function
· One place to check any enterprise data quality issues
· Reusability for update or access and consistency is both provided and required.
· Data Quality Rules which define Governance Policy are represented as declarative statements.
· Data Quality Rules are not hidden in, or bound in the code; they are visible and explicit data or metadata.
· Rules are dependent on situational context (this process, activity, object specialization) for situational integrity and service reusability (more situations).