Recently, I started analyzing the dependencies between data management operating models and various data architecture types (i.e., centralized and decentralized). In my practice, I use three types of data management operating models: centralized, decentralized, and hybrid. I’ve decided to check the opinion of DAMA-DMBOK2 on this subject. I was very much surprised when I found out the following:
1. DAMA-DMBOK2 distinguishes Data Governance (DG) from Data Management Operating models.
In Chapter 3, it describes DG operating models. In Chapter 16, you come across DM operating models. I could not find an explanation of the differences between these approaches. I guess different professionals have written these chapters, and no alignment has occurred afterward.
2. The number of models differs.
There are 3 Data Governance operating models: centralized, replicated, and federated. However, DAMA-DMBOK2 recognizes 5 Data Management operating models: decentralized, network, centralized, hybrid, and federated.
3. The models have similarities, even if they have different names.
For example, the centralized DG and DM models are similar. The Federated DG model is like the DM Hybrid and Federated models. The DG replicated model seems to be similar to the Decentralized DM model.
WHAT CAN YOU?
If you are a data management executive and need to develop or adjust the operating model for your company, I recommend you take the following steps.
1. Define the terminology used in your company.
The expected result of this stage is to define whether you talk about the “Data Governance” or “Data Management” operating model.
Unfortunately, we have unaligned definitions of data management and governance within the DM community.
I use the following DAMA-DMBOK2-based approach. Data governance (DG) is a data management (DM) capability. Data governance is a company’s ability to design a data management framework, coordinate its implementation, and control its performance. The data management framework (DMF) includes a DM operating model, organizational structure, regulations, roles, and processes and coordinates the DMF performance.
It is worth noting that “data governance” governs a “data management framework,” not “data.” You can watch a free webinar on this topic at the Data Crossroads Academy site.
2. Analyze different factors that influence the required operating model.
At the end of this step, you should identify the type of operating model your company needs. These factors are a company’s profile and data architecture type.
A company’s profile considers a company’s size, business model, geographic coverage, financial resources, etc. The DM or DG operating model will follow the business operating model. More about this topic you can find in this webinar.
3. Adjust the data management framework to the needs of the required operating model.
To be continued.
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