In this article, we compare DAMA-DMBOK and DCAM maturity models.

This article is the last in the “DAMA-DMBOK2 vs. DCAM® 2.2” series. In the first three articles, we have analyzed the statistics regarding the usage of these frameworks. Then we have made the general comparison of metamodels and have continued with the mapping between building blocks of different frameworks. Both frameworks allow assessing the maturity of data management functions.

This article will compare the approaches of DAMA-DMBOK2 and DCAM® 2.2 to measure the maturity of data management.

Our analysis starts with the identification of the comparison criteria. I have developed a framework for the comparison based on the maturity models by Carnegie Mellon University and the Institute of Internal Auditors. Let us take a look at it.

A framework to compare maturity models

The comparison framework includes the following three components:

  • The levels of maturity

The level of maturity indicates three characteristics:

    • The number of levels
    • The name
    • The method to identify an aggregated maturity level
  • Building blocks and their structures

Different models use different business blocks and their hierarchies. Processes, capabilities are examples of building blocks. The structure of components, capabilities, and sub-capabilities of the DCAM® 2.2 model is an example of a hierarchy.

  • Assessment criteria

Several different maturity models exist. This is the state-of-the-art to compare them. Considering the very different natures and backgrounds of these models, data management deliverables/outcomes/artifacts is one of the feasible factors to make a reasonable comparison. I have demonstrated such an approach in the previous article of this series.

Now let us make the comparison between DAMA-DMBOK and DCAM maturity models and approaches to assess the maturity. We will do it by using the described above comparison framework.

DAMA-DMBOK2 vs DCAM® 2.2 maturity models

●      The levels of maturity

The comparison between the number, names, and content of levels can be seen in Figure 1. I have put all characteristics in a table format to ease the comparison.

The comparison of the levels of maturities between DAMA-DMBOK2 and DCAM® 2.2 frameworks.

Figure 1. The comparison of the levels of maturities between DAMA-DMBOK2 and DCAM® 2.2 frameworks.

The comparison leads to several conclusions:

  • The number of levels is identical: Six.
  • The names are quite different. The levels are not comparable.

For example, the “Initial/Ad Hoc” level by DAMA-DMBOK2 is level 1. While DCAM® 2.2 put the “Ad-hoc” level to the level 0, “Non initiated.” It means that a company with the “Ad-hoc” status of data management activities will fall into different maturity levels depending on the chosen framework.

  • The approach to identifying the level of maturity.

Identifying the approach is a challenging exercise. The frameworks use different criteria for identification.

The DAMA-DMBOK2 model is rather consistent. The maturity is based on the level of the development of roles, processes, tools, data quality management, risks, and associated controls.

DCAM® 2.2 has another approach. It includes the consideration of the maturity in each  (sub)-capabilities. The method to aggregate the maturity levels of each (sub)-capability at the higher level of abstraction is unclear.

The second component of the comparison framework is building blocks.

●      Building blocks: DAMA-DMBOK2 vs DCAM® 2.2

We have already compared the building blocks of these two frameworks in the second article of this series.

I want to remind you of the differences.

DAMA-DMBOK2 elaborates on 11 Knowledge Areas. The DCAM® 2.2 model includes eight components, 38 capabilities, and 136 sub-capabilities. The building blocks of these two models differ by the number, content, and type of building blocks. Let’s take a quick look at Figure 2. I have used one of the diagrams of the “Orange” model.

DAMA-DMBOK2 Knowledge Areas vs DCAM® 2.2 components.

Figure 2. DAMA-DMBOK2 Knowledge Areas vs DCAM® 2.2 components.

Both frameworks have different viewpoints on data management. They have several building blocks similar by names: Data Governance, Data Architecture, Data Quality. In reality, the differences are even deeper. For example, the deliverables of Data Governance by DAMA-DMBOK2 quite differ from those by DCAM® 2.2 Data Governance.

I have provided an analysis of these contextual differences in the third article of this series. The last factor of the framework comparison is the assessment criteria.

●      Assessment criteria: DAMA-DMBOK2 vs DCAM® 2.2

DAMA-DMBOK2 offers four assessment criteria: Activity/Process, Tools, Standards, People, and Resources. DAMA-DMBOK2 recommends applying these assessment criteria to Knowledge Areas. It does not provide the methodology to perform such an assessment and aggregate the results per assessment criteria.

The methodology used by DCAM® 2.2 is also not fully clear, maybe because of restrictions for the publicly available materials.  Each of the sub-capability has a Rating Guidance based on 6 levels of maturity. A Rating Guidance describes the status of each sub-capability depending on its level of development. The method to derive the overall capability level per component is not clear.

In this article, I have compared only DAMA-DMBOK and DCAM maturity models. A couple of years ago, I analyzed 6 maturity models. The challenges with the data management maturity models brought me to the idea to apply the “Orange” model to perform the maturity assessment.

The “Orange” data management maturity assessment model

This approach allows the measuring of the data management at the different levels of abstraction. The key idea of the maturity assessment methodology, you can see in Figure 3.

The concept of the “Orange” data management maturity assessment.

Figure 3. The concept of the “Orange” data management maturity assessment.

Data management is a set of capabilities that enable the data chains to transform data into information. Data modeling, information system architecture, data quality, and data management frameworks are key data management capabilities. The model can also include other capabilities as well. Process, role, tools, resources, and data are key components that enable every capability. The methodology allows measuring the maturity level of each capability component. Then the results are automatically aggregated to the level of separate capabilities and the overall data management maturity.

Based on this methodology, Data Crossroads has developed a free-of-charge maturity scan. Since March 2019, more than 700 companies worldwide have performed this scan on an anonymous basis. A review of the results has been published in 2019 and 2020.

By now, we have finalized the analysis of the differences and similarities between DAMA-DMBOK2 and DCAM® 2.2 maturity models.


After the analysis, we can conclude the following:

  • The approaches to measuring data management maturity by DAMA-DMBOK2 and DCAM® 2.2 differ to a great extent.
  • The differences can be found in:
    • The number and content of the building blocks of the models
    • Assessment criteria
    • Methods to describe the maturity levels.
  • The method to aggregate the maturity levels to assess the overall maturity of a company or separate components is unclear for both frameworks.

This is the last article in the series devoted to the comparison of DAMA-DMBOK2 and DCAM® 2.2 frameworks.