Peter Aiken's framework uses the DMBoK functional areas to describe the situation in which many organizations find themselves. An organization can use it to define a way forward to a state where they have reliable data and processes to support strategic business goals. In trying to reach this goal, many organizations go through a similar logical progression of steps.

Phase 1: The organization purchases an application that includes database capabilities. This means the organization has a starting point for #datamodeling / design, #datastorage, and #datasecurity (e.g., let some people in and keep others out). To get the system functioning within their environment and with their data requires work on integration and interoperability.

Phase 2: Once they start using the application, they will find challenges with the quality of their data. But getting to higher quality data depends on reliable #Metadata and consistent #DataArchitecture. These provide clarity on how data from different systems works together.

Phase 3: Disciplined practices for managing #DataQuality, Metadata, and architecture require #DataGovernance that provides structural support for data management activities. Data Governance also enables execution of strategic initiatives, such as Document and #ContentManagement, #ReferenceDataManagement, #MasterDataManagement, #DataWarehousing, and #BusinessIntelligence, which fully enable the advanced practices within the golden pyramid.

Phase 4: The organization leverages the benefits of well-managed data and advances its analytic capabilities.

Aiken's pyramid draws from the DAMA Wheel, but also informs it by showing the relation between the Knowledge Areas. They are not all interchangeable; they have various kinds of interdependencies. The Pyramid framework has two drivers. First, the idea of building on a foundation, using components that need to be in the right places to support each other. Second, the somewhat contradictory idea that these may be put in place in an arbitrary order.