Data Crossroads summarized its implementation practices into the “Orange” Data Management Framework (DMF).
This framework includes:
- a data management (DM) capability model
- a DM maturity assessment model
- the “data management star” method to implementing a DM function
- the model and method to document data lineage and develop a knowledge graph of data assets
We shared the basics of these methodologies in our books and training courses offered in the DC Academy.
DMF has different goals and meanings depending on the level of organizational hierarchy: strategic, tactical, and operational.
A DMF aims to enhance the value of and control data assets at strategic and tactical levels. The DMF does it by establishing a data management function and internal regulatory documents such as policies, standards, processes, and roles.
The “Orange” DMF is a collection of models, methods, and templates that assist in establishing a data management business function and documenting data lineage.
The “Orange” DMF serves five purposes regarding a data management capability and function:
- Scoping and planning a data management initiative
The “Orange” DMF shares a business driver-oriented methodology. It helps a company define a feasible scope of the data management initiative and fit its needs, resources, and culture.
- Defining a data management strategy and designing capabilities
The “Orange” DMF elaborates on a data management capability model that includes five core capabilities and twenty-eight sub-capabilities, each detailed into the set of processes, policies and standards, deliverables, roles, and tools.
The “Orange” DMF provides templates for the policies, standards, and deliverables.
- Implementing a data management framework
The “Orange” DMF delivers the “data management star” implementation method. This method considers dependencies between various data management capabilities. It includes project management templates and time estimations. During the implementation of the DMF, a company produces multiple artifacts. The model of data lineage / a knowledge graph of data assets demonstrates how to link these artifacts.
- Monitoring performance
The “Orange” DMF offers a set of standard key performance indicators to measure implementation and operational performance.
- Assessing results and planning the future
The “Orange” DMF provides several methods for measuring data management maturity. By comparing desired and achieved outcomes, a company identifies gaps and plans actions to further DM function development.
Data lineage is a description of data movements and transformations at various abstraction levels along data chains and relationships between data at these levels. Data lineage ensures the traceability and transparency of data processing, transformation, and integration.
Data lineage helps a company to comply with various legislative requirements, support multiple business and IT changes, and reduce IT maintenance costs.
In our consulting journey, we realized that the implementation of a data management framework and data lineage documentation are two sides of the same coin:
The implementation of a data management framework follows the logic of data lineage documentation and vice versa.
We developed a data lineage metamodel based on the analysis of various industry guidelines and legislations. This model allows linking all DM capabilities and their artifacts. In this context, this data lineage metamodel also serves the purpose of documenting a knowledge graph of data assets. We use this metamodel in our practices.