At its most basic definition, information architecture is the construction of a structure or the organization of information. An Information Architecture is the “blueprint” of an enterprise expressed in terms of information models which show what information resources are required; their processes and information, and the infrastructure and processes required to manage and store them.

Information architecture defines how data is stored, managed, and used in a system. In particular, information architecture describes how data is persistently stored and how components and processes reference and manipulate this data. The information architecture describes how external/legacy systems will access the data, and includes descriptions or diagrams of interfaces to data managed by external/legacy systems.

Last but not least, the information architecture includes information regarding implementation of common data operations. Why this article now?

What is really new in the last 5 years?

I was recently horrified when researching trends on IA for my recent Architecture Boot Camp course. The first page of results when searching on “Information Architecture” on Google referred to website content management. Information Architecture is NOT website content management and website content organization, although these are an important part of it. Another recent trend is to include directory data structure and identity management within IA — caused by the proliferation of data driven security access and LDAP databases supporting our applications.

In a nutshell, the over simplified most prevalent benefit of Information Architecture is the enablement of rapid business decision making. Without linkage to the business architecture, information architecture really can’t exist on its own. We must first understand business architecture, and then use it to create our information architecture.

In many of the architecture presentations and courses I have taught, I speak about the linkages between business and information. I usually suggest to those building architectures that there is no value in architecture until these linkages are expressed in terms of models and architecture diagrams. Linkages can also be understood as relationships between the business and information. Businesses essentially want answers to assist in their business initiatives, and these answers in terms of information technology lie in the data, in one form or another.

For decades of history in information technology, the primary goal of technology is to move data from point A to point B, from one format to another. We spend billions of dollars each year to do this one task, and a very prevalent, popular and recent advancement is that of data warehousing. The value of data warehousing is held in the quality of the data, which is achieved not through extraction, but in the transformation of the data.

Transformation of data is a costly and time-consuming process.

We have the best chance of being successful with all of the efforts needed to continue to transform and collect data if we have a solid Information Architecture. Solid means that is has been well planned and designed. Solid also means that we have architected out points that may prove inflexibility, and architected in ways to embrace changes in our business and technology.

Solid information architecture can also be termed as one that is mature. Maturity is achieved through the development of various levels of structures and processes to a point where they are understandable, achievable and repeatable.

A quick laundry list of the levels included within a mature Information Architecture:

Highest Level: An information environment, which includes an organizational culture around information, as well as information strategies. The strategies include planning and maintaining relationships from business to information through structures and technology. It also includes data governance at the highest levels.

Second Level: The Enterprise Information Architecture which includes Information principles, rules for detailed information governance and sharing, information content design, and linkage to the Business Architecture.

Third Level: Information Management which includes Data Stewardship, Information Security and Access tools, processes and procedures, Extraction and Transition and Loading Strategies, Database Server Administration Policies & Guidelines, Data Quality and Integrity Rules, Data Definition Standards, Dictionaries and Content Indices.

Fourth Level: At the most granular level, the Information Architecture contains the information architecture made up of databases, data warehouses, logical, physical & data warehouse data models, backup and recovery procedures, database execution scripts, meta-data management, data performance and auditing, etc.

We can hope that those who are in technology positions within our IT departments can look beyond content. We hope that they can use this as an example that a simple “Google” search does not provide the true definition or meaning behind a technical topic in the first page of results. Databases, models, structure and governance were around far longer than web page content and all are needed to even store the content!