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| Business Intelligence Series |
The holy grail of building a Data Analytics infrastructure seems to be nowadays the creation of a data mesh, a decentralized data architecture that organizes data by specific business domains. This endeavor proves to be difficult to achieve given the various challenges faced – data integration, data ownership, data product creation and ownership, enablement of data citizens, respectively enforcing security and governance in a federated manner.
Microsoft Fabric promises to facilitate the creation of data mashes with the help of domains and subdomain by providing built-in security, administration, and governance features associated with them. A domain is a way of logically grouping together all the data in an organization that is relevant to a particular area or field. A subdomain is a way for fine tuning the logical grouping of the data.
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| Business domains & their entities |
At high level the challenge of building a data mesh is on how to match or aggregate structures. On one side is the high-level structure of the data mesh, while on the other side is the structure of the business data entities. The data entities can be grouped within a taxonomy with multiple levels that expands to the departments. That’s why it seems somehow natural to consider the departments as the top-most domains of the data mesh. The issue is that if the segmentation starts from a high level, iI becomes inflexible in modeling. Moreover, one has only domains and subdomains, and thus a 2-level structure to model the main aspects of the data mesh.
Some organizations allow unrestricted access to the data belonging to a given department, while others breakdown the access to a more granular level. There are also organizations that don’t restrict the access at all, though this may change later. Besides permissions and a way of grouping together the entities, what value brings to set the domains as departments?
Therefore, I’m not convinced about using an organizations’ departmental structure as domains, especially when such a structure may change and this would imply a full range of further changes. Moreover, such a structure doesn’t reflect the span of processes or how permissions are assigned for the various roles, which are better reflected on how information systems are structured. Most probably the solution needs to accommodate both perspective and be somehow in the middle.
Take for example the internal structure of the modules from Dynamics 365 (D365). The Finance area is broken down in Accounts Payable, Accounts Receivables, Fixed Assets, General Ledger, etc. In some organizations the departments reflect this delimitation to some degree, while in others are just associated with finance-related roles. Moreover, the permissions are more granular and, reflecting the data entities the users work with.
Conversely, SCM extends into Finance as Purchase orders, Sales orders and other business documents are the starting or intermediary points of processes that span modules. Similarly, there are processes that start in CRM or other systems. The span of processes seem to be more appropriate for structuring the data mesh, though the system overlapping with the roles involved in the processes and the free definition of process boundaries can overcomplicate the whole design.
It makes sense to define the domains at a level that resembles the structure of the modules available in D365, while the macro data-entities represent the subdomain. The subdomain would represent then master as well as transactional data entities from the perspective of the domains, with there will be entities that need to be shared between multiple domains. Such a structure has less chances to change over time, allowing more flexibility and smaller areas of focus and thus easier to design, develop, test, deploy and maintain.
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