Is data architect a role that’s interchangeable with enterprise architect? Many observers see the two roles are overlapping to some degree. However, perhaps it’s time that data architecture be recognized for having a distinct role in today’s enterprises.

With the rise of service oriented architecture and distributed computing, enterprise architects have been emerging as key players in their organizations – assuring that applications and systems are designed within a coherent framework and follow a roadmap designed with the business in mind. Now, the same discipline needs to apply to an enterprise’s data resources. A data architect, as defined within Wikipedia, is a person “responsible for ensuring that the data assets of an organization are supported by an architecture supporting the organization in achieving its strategic goals. The architecture should cover databases, data integration and the means to get to the data. Usually the data architect achieves his/her goals via setting enterprise data standards.”

The Wikipedia passage also notes that data architects also are often referred to as “data modelers.” However, perhaps it’s time to start clearing up the confusion about the data architect’s role – because organizations are going to need them more than ever.

In a new post over at Intelligent Enterprise, Rajan Chandras takes on such perceptions, arguing that data architects have distinct and very important roles to play within today’s information-rich enterprise. He states that the role of data architect has long been an under-appreciated, yet essential specialty that will play an increasingly important role in today’s emerging analytic enterprise..

Data architecture has been around for quite some time as its own discipline, Chandras observes – as “a lynchpin of the entire software application.” However, data architecture too often is being overlooked, and those practicing data architecture – whether of not they are “data architects” by name – have “a difficult time justifying their presence on a project and getting the tools they need to deliver to expectations.”

Trouble is, the jobs of data architects have grown only more critical as time has gone on. Organizations seek to compete on analytics, and decision makers are demanding real-time access to the state of their business. Newer approaches such as service oriented architecture, Enterprise 2.0, and cloud computing are exposing data from all corners of the enterprise and beyond. However, these efforts will fall flat on their faces if the data they pulse through their systems is not trustworthy, not timely, or of dubious quality.

Add to that countless enterprise data management initiatives: master data management, data warehousing, business intelligence, event processing, business rules management, business process management, decision management, and compliance reporting.

Are organizations elevating their data architect roles to address all these new opportunities and challenges?  Not really, Chandras says:

“In the midst of this maelstrom stands the beleaguered data architect, alone and unappreciated. Even as millions of dollars are burnt up all around him (or her) in repeated tragicomic parodies of project management and solution architectures, the data architect – the unseen force holding together the protons and neutrons of data in the nucleus of IT solutions — must struggle to justify her (or his) existence.”

The role of data and information is critical to today’s organizations, which need to compete on analytics. Decision-makers in organizations can’t be sifting through data willy-nilly. Data architects can assure that the information is credible and well-maintained.

As Chandras puts it: “data architecture is a crucial piece of the software, and an experienced data architect is a critical success factor for any software project.” And, he adds, “If you don’t have one in-house, run to the nearest consulting shop and get one.”

Data architects address key areas not covered by enterprise architects. However, there are skills and qualities the two categories have in common. In a post here at the Perspectives site in 2008, I discussed the five essential qualities an enterprise architect needs to bring with him or her to the job. These qualities apply equally to data architects as well. Not how in both cases, “people” skills trump technical skills:

1) Well-respected and influential. This is essential for getting projects moving through the organization. Data architects need the support of senior IT and business managers and the ability to influence them as well as the IT organization at large.

2) Able to emphasize methodology, modeling, and governance. As is the case with EAs, individuals with limited knowledge may be pressed into data architect roles. A data architect needs to be well-versed in the architectural and modeling principles that support data management.

3) Technologically and politically neutral. Good architects must be vendor/product-neutral and maintain an objective perspective. Likewise, it is important to understand enough about the broad range of technologies that an architect can engage in discussion with technical experts and not be swayed by inappropriately biased personal agendas in technical decisions.

4) Articulate, persuasive, and a good salesperson. Data architects must spend substantial time communicating and educating – they need appropriate skills to clearly communicate ideas in a persuasive, compelling manner. They also need to be able to talk tech with developers, as well as talk business with CEOs and CFOs.

5) Enthusiastic. Data architects should have a passion for life, work, and data architecture. They need to thoroughly believe in their mission to help the enterprise take advantage of information to move ahead in the market.