Data Architecture and Information Architecture: What’s the Difference?

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Many people in the IT and Data Management industries claim there’s no real difference between the terms Data Architecture (DA) and Information Architecture (IA). In a recent DATAVERSITY™ survey, almost half the respondents said they define DA and IA as the same concept. Others say the two terms should be applied to two very different approaches toward integrating an enterprise’s IT functions.

They tend to agree that whichever you do, and whatever you call it, your organization should consider starting it now, if you’ve not already done so. The stakes, and the potential rewards, are often just too high.

Many IT experts use “data” to denote the raw numbers, names, addresses, and other abstracted contents that used to fall under the purview of “data processing” back during the mainframe and early PC eras. Back when computational power was limited and expensive, it was enough of a miracle just to get an organization’s finances, payroll, and mailing lists into digital form.

But these days, IT departments can do a lot more than simply crunch numbers and update addresses. They can find hidden relations among different data. They can help you gain a better view of your organization’s activities, strengths, and opportunities. And if you’re not using these larger capabilities, your competitors just might be.

That, say the advocates of Information Architecture, is what they mean by “Information.” They define information as a superset of data; something bigger, vaster.

The Data Management Association’s “DAMA Guide to the Data Management Body of Knowledge” posits a top-to-bottom hierarchy of knowledge, information, and data. Data, the guide says, “is the representation of facts as text, numbers, graphics, images, sound or video.”

Information, according to DAMA, is “data in context. Without context, data is meaningless; we create meaningful information by interpreting the context around data… The resulting information then guides our decisions.”

A white paper by the State Department of Public Works in Queensland, Australia on Information Architecture gives the following definitions:

“Information is any collection of data that is processed, analyzed, interpreted, organized, classified or communicated in order to serve a useful purpose, present facts or represent knowledge in any medium or form. This includes presentation in electronic (digital), print, audio, video, image, graphical, cartographic, physical sample, textual, or numerical form. Information architecture is the means of providing a structured description of an enterprise’s information, the relationship of this information to business requirements and processes, applications and technology, and the processes and rules which govern it.”

That paper also defined four basic types of “Information”:

  • Transactional (“Structured content that supports business processes and workflows and is implemented using structured databases”);
  • Analytical (“Structured content that supports queries and analysis and is implemented using structured databases, [and which] will contain aggregated or derived information”);
  • Authored (“Unstructured content in a wide variety of formats, such as multimedia, application system programs, or text documents with embedded graphics”);
  • Published (“Unstructured content assembled from its component pieces, into a desired format and disseminated to a target audience and implemented using technologies that optimize discovery, search and retrieval”).

Within these definitions, one can imagine many types of documents that would now count as data, to be integrated and interpreted into information: a legal department’s briefs and case research; PR releases, advertisements, and promotional web pages; emails, both internal and external; SharePoint message threads; Social-media messages; Security-camera images.

A 2011 Sybase white paper “What’s In YOUR Architecture?,” depicts a five-level pyramid of “domains of enterprise architecture.” The figure starts at the top with Business and descends through Information, Applications, Data, and Technology.

This Sybase paper defines Information Architecture as “a holistic view on the flow of information in an enterprise, including the effects of the processes that act upon the data.”

Data Architecture, meanwhile, is defined as describing “the way data will be processed and stored; how the data flows and is used by the project teams, including the data models (conceptual, logical, physical, and dimensional).”

In these definitions, not only is information something larger in scope than data, but IA is a set of tasks and procedures hierarchically higher than DA:

“Data Architecture (DA) is a component of Information Architecture, and is concerned with the design and use of data in structured formats such as databases and file systems. A data architect models the data in stages (conceptual, logical and physical) and must relate the data to each process that consumes (uses) that data.”

Another Sybase white paper, written by Richard Ordowich in 2011, describes IA as the underlying basis of all of an enterprise’s IT operations, and as the first principle in enterprise IT design:

“The information architecture is the starting point for data modeling, design, and development to support business process needs… any new models or changes to existing models must be consistent with the definitions of existing information objects.”

Ordowich also differentiates IA from “a collection of data models,” because it imposes “coherence and consistency in both the definition and use of common data objects.” This consistency extends from “the granular aspects of business structure” to “the global view and framework in which business processes utilize those data concepts.”

Mike Walker, a senior enterprise architecture advisor and strategist at Hewlett-Packard, has an online essay in which he parses different definitions of IA and then concludes with his own:

“Information Architecture is an aspect of enterprise architecture that enables an information strategy or business solution through the definition of the company’s business information assets, their sources, structure, classification and associations that will prescribe the required application architecture and technical capabilities.”

Why would a profession that depends on precision and exactness, in nomenclature as in every other aspect of its work, disagree on defining a major term like IA? It could be because different organizations, and different units within the same organizations, have evolved different ways of handling their data and/or information over the years. That’s also one reason why you may need to impose a consistent architecture onto your organization’s data.

Organizations that have come together by mergers and acquisitions, and even different units within the same organizations, need to conform different data formats and systems under enterprise-wide standards, for total interoperability and integration. That’s what Data Architecture does. And it’s important. But, its advocates claim, Information Architecture can be even more important.

Analyzing the DATAVERSITY survey mentioned at the top of this piece, David Loshin and Charles Roe repeat the common mantra that “data is the lifeblood, the glue, the bricks, and the gold of the modern enterprise.”

But then they add:

“Information is data put into action. Where a specific data element may exist on a server somewhere in one format or another, it has lesser business value until it is integrated with other data elements into an information package. Information is data with context. So where Data Architecture is necessary to contain and organize the manifold data resources into a manageable system, Information Architecture is necessary to combine those resources into a structure that allows the dissemination of that information to be captured, shared, analyzed, utilized, and governed throughout an enterprise, across all lines of business, within all departments, with confidence and reliability.”

Or, in the words of enterprise data consultant Natty Gur, “Information is truly the bridge between business and IT.”

Read more about Data Architecture, click here.

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