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| Data Migrations Series |
Auditability
Auditability is the degree to which the solution allows checking the data for their accuracy, or for their quality in general, respectively the degree to which the DM solution and processes allow to be audited regarding compliance, security and other types of requirements. All these aspects are important in case an external sign-off from an auditor is mandatory.
Automation
Automation is the degree to which the activities within a DM can be automated. Ideally all the processes or activities should be automated, though other requirements might be impacted negatively. Ideally, one needs to find the right balance between the various requirements.
Cohesion
Cohesion is the degree to which the tasks performed by the solution, respectively during the migration, are related to each other. Given the dependencies existing between data, their processing and further project-related activities, DM imply a high degree of cohesion that need to be addressed by design.
Complexity
Complexity is the degree to which a solution is difficult to understand given the various processing layers and dependencies existing within the data. The complexity of DM revolve mainly around the data structures and the transformations needed to translate the data between the various data models.
Compliance
Compliance is the degree to which a solution is compliant with internal or external regulations that apply. There should be differentiated between mandatory requirements, respectively recommendations and other requirements.
Consistency
Consistency is the degree to which data conform to an equivalent set of data, in this case the entities considered for the DM need to be consistent to each other. A record referenced in any entity of the migration need to be considered, respectively made available in the target system(s) either by parametrization or migration.
During each iteration, the data need to remain consistent, so it can facilitate the troubleshooting. The data are usually reimported between iterations or during same iteration, typically to reflect the changes occurred in the source systems or other purposes.
Coupling
Data coupling is the degree to which different processing areas within a DM share the same data, typically a reflection of the dependencies existing between the data. Ideally, the areas should be decoupled as much as possible.
Extensibility
Extensibility is the degree to which the solution or parts of the logic can be extended to accommodate further requirements. Typically, this involves changes that deviate from the standard functionality. Extensibility impacts positively the flexibility.
Flexibility
Flexibility is the degree to which a solution can handle new requirements or ad-hoc changes to the logic. No matter how good everything was planned there’s always something forgotten or new information is identified. Having the flexibility to change code or data on the fly can make an important difference.
Integrity
Integrity is the degree to which a solution prevents the changes to data besides the ones considered by design. Users and processes should not be able modifying the data besides the agreed procedures. This means that the data need to be processed in the sequence agreed. All aspects related to data integrity need to be documented accordingly.
Interoperability
Interoperability is the degree to which a solution’s components can exchange data and use the respective data. The various layers of a DM’s solutions must be able to process the data and this should be possible by design.
Maintainability
Maintainability is the degree to which a solution can be modified to or add minor features, change existing code, corrects issues, refactor code, improve performance or address changes in environment. The data required and the transformation rules are seldom known in advance. The data requirements are definitized during the various iterations, the changes needing to be implemented as the iterations progress. Thus, maintainability is a critical requirement.
