Data view architecture document

This chapter describes the Data Architecture part of Phase C.

Objective

The objective here is to define the major types and sources of data necessary to support the business, in a way that is:

• Understandable by stakeholders
• Complete and consistent
• Stable

It is important to note that this effort is not concerned with database design. The goal is to define the data entities relevant to the enterprise, not to design logical or physical storage systems. (However, linkages to existing files and databases may be developed, and may demonstrate significant areas for improvement.)

Approach

Enterprise Continuum

As part of this phase, the architecture team will need to consider what relevant Data Architecture resources are available in the organization's Enterprise Continuum; in particular, generic data models relevant to the organization's industry "vertical" sector. For example:

• ARTS has defined a data model for the Retail industry.
• POSC has defined a data model for the Petrotechnical industry.

Gap Analysis

A key step in validating an architecture is to consider what may have been forgotten. The architecture must support all of the essential information processing needs of the organization. The most critical source of gaps that should be considered is stakeholder concerns that have not been addressed in architectural work.

Types of data gap:

• Data not located where it is needed
• Not the data that is needed
• Data not available when needed
• Data not created
• Data not consumed
• Data relationship gaps
• etc.

Gap analysis highlights shortfalls in data services and/or data elements that have been accidentally left out, deliberately eliminated, or are yet to be defined. Gap Analysis Matrix in Phase D illustrates an example of a gap analysis matrix. The suggested steps are as follows:

• Draw up a matrix with all the Data Architecture Building Blocks of the Baseline Architecture on the vertical axis, and all the Data Architecture Building Blocks of the Target Data Architecture on the horizontal axis. In creating the matrix, it is imperative to use terminology that is accurate and consistent.
• Add to the Baseline Architecture axis a final row labeled "New Data Architecture Building Blocks", and to the Target Architecture axis a final column labeled "Eliminated Data Architecture Building Blocks".
• Where a Data Architecture Building Block is available in both the Baseline and Target Architectures, record this with "Included" at the intersecting cell.
• Where a Data Architecture Building Block from the Baseline Architecture is missing in the Target Architecture, each must be reviewed. If it was correctly eliminated, mark it as such in the appropriate "Eliminated" cell. If it was not, you have uncovered an accidental omission in your new architecture that must be addressed by reinstating the Data Architecture Building Block in the next iteration of the architecture design - mark it as such in the appropriate "Eliminated" cell.
• Where a Data Architecture Building Block from the Target Architecture cannot be found in the Baseline Architecture, mark it at the intersection with the "New" row, as a gap that needs to filled, either by defining or inheriting the building block.

When the exercise is complete, anything under "Eliminated Services" or "New Services" is a gap, which should either be explained as correctly eliminated, or marked as to be addressed by reinstating or developing/procuring the function.

Inputs

Inputs to this phase are:

• Data principles (Data Principles), if existing
• Request for Architecture Work (Request for Architecture Work)
• Statement of Architecture Work (Major Output Descriptions)
• Architecture Vision (Business Scenario/Architecture Vision)
• Relevant technical requirements that will apply to this phase
• Gap analysis results (from Business Architecture)
• Baseline Business Architecture, Version 1.0 (detailed), if appropriate
• Target Business Architecture (Business Architecture), Version 1.0 (detailed)
• Baseline Data Architecture, Version 0.1, if available
• Target Data Architecture, Version 0.1, if available
• Re-usable building blocks, from organization's Enterprise Continuum (Introduction to the Enterprise Continuum), if available (in particular, definitions of current data)

Steps

1. Develop Baseline Data Architecture Description Develop a Baseline Description of the existing Data Architecture, to the extent necessary to support the Target Data Architecture. The scope and level of detail to be defined will depend on the extent to which existing data elements are likely to be carried over into the Target Data Architecture, and on whether existing architectural descriptions exist, as described in Approach . To the extent possible, identify the relevant Data Architecture building blocks, drawing on the Architecture Continuum, and review/verify the following primitives from the Zachman Framework:
   • Business data model (entities, attributes, and relationships) Entity-relationship diagrams illustrating views of the Data Architecture to address the concerns of stakeholders.
   • Logical data model (logical views of the actual data of interest from the applications point of view)
   • Data management process models, including:
     1. Data dissemination view
     2. Data lifecycle view
     3. Data security view
     4. Data model management view
     1. Review and validate (or generate, if necessary) the set of data principles. These will normally form part of an overarching set of architecture principles. Guidelines for developing and applying principles, and a sample set of data principles, are given in Part IV: Resource Base, Architecture Principles .
     2. Select relevant Data Architecture resources (reference models, patterns, etc.) from the Architecture Continuum, on the basis of the business drivers, and the stakeholders and concerns.
     3. Select relevant Data Architecture viewpoints (for example, stakeholders of the data - regulatory bodies, users, generators, subjects, auditors, etc.; various time dimensions - real-time, reporting period, event-driven, etc.; locations; business processes); i.e., those that will enable the architect to demonstrate how the stakeholder concerns are being addressed in the Data Architecture.
     4. Identify appropriate tools and techniques (including forms) to be used for data capture, modeling, and analysis, in association with the selected viewpoints. Depending on the degree of sophistication warranted, these may comprise simple documents or spreadsheets, or more sophisticated modeling tools and techniques such as data management models, data models, etc. Examples of data modeling techniques are:
        • IDEF
        • Object Role Modeling
     1. For each viewpoint, create the model for the specific view required, using the selected tool or method. Examples of logical data models are:
        • The C4ISR Architecture Framework Logical Data Model
        • ARTS Data Model for the Retail industry
        • POSC Data Model for the Petrotechnical industry
     2. Assure that all stakeholder concerns are covered. If they are not, create new models to address concerns not covered, or augment existing models (see above). Model the following:
        1. Business data model (entities, attributes, and relationships) Draw entity-relationship diagrams to illustrate views of the Data Architecture to address the concerns of stakeholders.
        2. Logical data model (logical views of the actual data of interest)
        3. Data management process models, including:
           • Data dissemination view
           • Data lifecycle view
           • Data security view
           • Data model management view
        4. Relate data entities to business functions in the Business Architecture, indicating which of the CRUD operations (Create, Reference, Update, and Delete) are performed by which functions.
           • Relate each lowest-level business function in the Business Architecture to the set of data entities, indicating which of the CRUD operations (Create, Reference, Update, and Delete) are performed by the function concerned.
           • Generate entity-business function matrices tabulating all the relationships.
           • Review and validate the entity-business function matrices, checking that each entity is created by at least one function, and referenced or updated by at least one other function.
           • Time permitting, relate entities to the application systems described in the Baseline Applications Architecture Description.
        1. Identify required building blocks and check against existing library of building blocks, re-using as appropriate.
        2. Where necessary, define new Data Architecture Building Blocks.
        • Business data model
        • Logical data model
        • Data management process model
        • Data entity/business function matrix
        • Data interoperability requirements (e.g., XML schema, security policies)

        If appropriate, use reports and/or graphics generated by modeling tools to demonstrate key views of the architecture. Route the Data Architecture document for review by relevant stakeholders, and incorporate feedback.

        1. Identify any areas where the Business Architecture (e.g., business practices) may need to change to cater for changes in the Data Architecture (for example, changes to forms or procedures, application systems, or database systems). If the impact is significant, this may warrant the Business Architecture being revisited.
        2. Identify any areas where the Applications Architecture (if generated at this point) may need to change to cater for changes in the Data Architecture (or to identify constraints on the Applications Architecture about to be designed). If the impact is significant, this may warrant the Applications Architecture being revisited, if already developed in this cycle.
        3. Identify any constraints on the Technology Architecture about to be designed.
        4. Refine the proposed Data Architecture only if necessary.
        1. Create gap matrix as described above.
        2. Identify building blocks to be carried over, classifying as either changed or unchanged.
        3. Identify eliminated building blocks.
        4. Identify new building blocks.
        5. Identify gaps and classify as those that should be defined and those inherited.

        Outputs

        The outputs of this phase are:

        • Statement of Architecture Work (Major Output Descriptions), updated if necessary
        • Baseline Data Architecture, Version 1.0, if appropriate
        • Validated data principles (Data Principles), or new data principles (if generated here)
        • Target Data Architecture, Version 1.0
          • Business data model
          • Logical data model
          • Data management process models
          • Data entity/business function matrix
          • Data interoperability requirements
          • Data dissemination view
          • Data lifecycle view
          • Data security view
          • Data model management view
          • Areas where the Business Architecture may need to change to cater for changes in the Data Architecture
          • Identify any areas where the Applications Architecture (if generated at this point) may need to change to cater for changes in the Data Architecture
          • Constraints on the Technology Architecture about to be designed

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