(Enterprise) Data Architecture 101

I loath the misuse of the term 'Data Architecture' by most software/consultancy/technology firms.
I loath the misuse of the term 'Data Architecture' by the average Enterprise Architect.

This is a blogpost that attempts to clarify the term 'Data Architecture'. And I do not want to complicate things, so lets just quote DAMA and its Body of Knowledge that extends the term to Data Architecture Management:

Data Architecture Management is the process of defining and maintaining specifications that:

• Provide a standard common business vocabulary,
• Express strategic data requirements,
• Outline high level integrated designs to meet these requirements, and
• Align with enterprise strategy and related business architecture.
  
  Data architecture is an integrated set of specification artifacts used to define data requirements, guide integration and control of data assets, and align data investments with business strategy. It is also an integrated collection of master blueprints at different levels of abstraction. 

The DAMA Body of Knowledge also defines Enterprise Data Architecture. Aye, dear Enterprise Architect, do you have an Enterprise Data Architecture?

Enterprise data architecture is an integrated set of specifications and documents. It includes three major categories of specifications:

1. The enterprise data model: The heart and soul of enterprise data architecture,
2. The information value chain analysis: Aligns data with business processes and other enterprise architecture components, and
3. Related data delivery architecture: Including database architecture, data integration architecture, data warehousing / business intelligence architecture, document content architecture, and meta-data architecture.
   
   Enterprise data architecture is really a misnomer. It is about more than just data; it is also about terminology. Enterprise data architecture defines standard terms for the things that are important to the organization–things important enough to the business that data about these things is necessary to run the business. These things are business entities. Perhaps the most important and beneficial aspect of enterprise data architecture is establishing a common business vocabulary of business entities and the data attributes (characteristics) that matter about these entities. Enterprise data architecture defines the semantics of an enterprise. 

I would like to point out two additions to these descriptions; 1) business rules management, although that comes with the territory if you model information (but loads of people do not get that). 2) (Enterprise) Data Architecture needs to be clearly aligned with data management and data governance. Getting them aligned results in relevant (&acceptable) data quality.

Please note that my definition of quality is; quality is value to some person. This definition deviates from the general (ISO) definition. If you want to know more, please read this blogpost I wrote a year ago. 

 Please note that my little 101-data-triangle deviates from the DAMA management functions. I think that the quality of data should play the lead part, all others (management, architecture, governance) are supportive. 

 
And to those that think that in a world of increasing datafication, Enterprise Data Architecture is not a part of Enterprise Architecture:

• Your organisation will miss out on opportunities that will never be discovered;
• Your organisation will have a hard time leveraging exciting innovative technology in the data-space;
• Your organisation will see an ever-increasing technical debt;
• Your organisation will suffer operational risks and privacy violations;
• Your organisation will have increasing costs associated with getting data cleansed and integrated downstream (ETL, data muddling, master data management blabla suites, business glossaries that are not aligned to actual data processes, data quality, loads of crappy data warehouses, etc..).

And to those that think that Enterprise Data Architecture is not part of Enterprise Architecture - brush up on your TOGAF, Zachman or whatever you're using - because your lagging. 

My final message to those that think that Enterprise Data Architecture is not part of Enterprise Architecture; you're nuts.