1. Issue
2. Business Asset Types
2.1. Glossary/vocabulary
2.1.1. Asset Types
2.1.1.1. Business Term
2.1.1.2. Acronym
2.1.1.3. KPI
2.1.2. Collects definitions (glosses)
2.1.3. Part of
2.1.3.1. Business Glossary Case.
2.1.4. Managed by the Business Semantics Glossary
2.2. Business Asset Domain
2.2.1. Asset Types
2.2.1.1. Report
2.2.1.2. Dimension
2.2.1.2.1. Data Quality Dimension
2.2.1.3. Metric
2.2.1.3.1. Data Quality Metric
2.2.1.4. Business Process
2.2.1.5. Learn what these mean
2.2.2. Part of the
2.2.2.1. Data Quality Case.
3. In my own words
3.1. You farm ants.
3.2. Ant farms are organised by species.
3.3. Ants of the same species work together, even if they are not in the same ant farms.
3.3.1. Ant species are communities.
3.3.2. Ant farms are domains.
3.4. In a domain, there are many types of ants, with very different jobs.
3.4.1. Governing ants
3.4.2. Data ants
3.4.3. Technology Ants.
3.4.4. Business Ants.
3.4.5. Ants who explain how one thing links to another. - Relationship ants.
3.4.6. Ants who report problems - Issue ants.
3.5. Each of these jobs have sub-more specific jobs. But they all fit broadly into these categories.
3.6. However, you control the ants, you can assign them jobs. These are just the usual jobs ants have.
3.7. Everything is an ant.
3.8. Ants are assets
4. Governance Asset Type Governance Asset Domain
4.1. Policy
4.1.1. E.g. Change of Address in the US
4.1.2. Policies are set up to meet the agreements of the Data Governance Council.
4.1.3. Policies are written to achieve the desired direction of metadata management.
4.2. Rule
4.2.1. Business Rule
4.2.1.1. Business Rules may apply to people, processes, corporate behavior and computing systems.
4.2.1.2. Business Rules are put in place to help the organization achieve its **Policies**
4.2.1.3. A Business Rule is a rule of an organization that defines or constrains some aspect of business and always resolves to **either true or false.**
4.2.1.3.1. What does this mean?
4.2.1.4. Note that a Business Rule is qualitative. E.g., the conditions "too low" and "preferred" for the two above examples are qualitative.
4.2.1.4.1. To know the quantitative meaning of "too low", we have to further decompose a Business Rule into one or more **Data Quality Rules**.
4.2.1.5. Business Rules can implement more than one **Policy.**
4.2.1.6. Business Rules
4.2.1.6.1. implement (make happen)
4.2.1.6.2. Applies to (affects)
4.2.2. Data Quality Rule
4.2.2.1. Turns Qualitative, abstract Business Rules into Quantitative, measurable rules. Quantitatively, how can these rules be met?
4.2.2.2. Sometimes called Data Profiling
4.2.2.3. They predicate requirements for Business Rules
4.2.2.3.1. predicate - predefine
4.2.2.4. Example
4.3. Supports Policy and Rule Management Case
4.3.1. Unfinished
5. Data Asset Type
5.1. Codelist
5.1.1. Asset Types
5.1.1.1. Code set
5.1.1.1.1. Code Value
5.2. Mapping Domain
5.2.1. Crosswalk
5.2.1.1. used in a Reference Data Management Case;
5.2.2. MappingSpecification
5.2.2.1. for use in a Data Dictionary Case.
5.2.3. Supports
5.2.3.1. Data Dictionary Case
5.2.3.2. Reference Data Management Case.
5.3. Data Asset Domain
5.3.1. Data Structure, with more specific types:
5.3.1.1. DataModel
5.3.1.2. DataEntity
5.3.1.3. DatabaseTable
5.3.2. Supports the Data Dictionary Case
5.4. Data Element, with more specific types:
5.4.1. DataAttribute
5.4.1.1. Attributes
5.4.2. TableColumn
6. Technology Asset Type
6.1. Technology Asset Domain
6.1.1. System
6.1.2. Database
6.1.3. (See also Technology Assets.)
7. Missing
7.1. Tableau workbook
7.2. Tableeau Project
7.3. Tableau Server
7.4. KPI
7.5. Tableau Data Source
7.6. Schema
7.7. Business Dimension
7.7.1. ???
7.8. Standard
7.8.1. ???