Data management today is a collection of disciplines (plural) that include mathematics, philosophy, logics, sociology, and so on. It has not yet become a formal profession, in spite of what many people declare. Data management professionals cannot self-proclaim that a formal data management profession exists. They must work hard at building a formal profession, and earning recognition and respect for that profession.
When the DAMA International Foundation was established in 2004, the primary initiative was to create a formal, certified, recognized, and respected data management profession. The objective for that initiative was to manage data as a critical resource of the organization. The theme was for data management professionals to develop a formal data management profession. That initiative was placed in the Introduction to DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK). Although we are working toward achieving that initiative, we have not come close to fully achieving that initiative.
The primary question has been How do you go about building a formal data management profession from a collection of disciplines? Three different approaches could be followed.
The first approach is a current hype-cycle approach that documents, publishes, and promotes all the current hype-cycles and terms that exist today. The approach is to join the current hype-cycles, support those hype-cycles, and perpetuate those hype-cycles. When hype-cycles run their course and change, the approach changes to support the new hype-cycles. The profession changes accordingly, the certifications change according, and the classes, books, articles, and consulting change accordingly. Eventually, by a very circuitous route, a formal data management profession may ultimately be achieved, but the cost to organizations along the way is tremendous.
The current hype-cycle approach is an easy route to follow. All that needs to be done is to keep track of the current hype-cycles, and the corresponding terms, and continue documenting, publishing, and promoting those current hype-cycles. Organizations and data management professionals look good, because they appear to be right on course with the current trends. However, over time the trends fail to provide the intended benefits, the data resource becomes more disparate, the trends fail, and new trends emerge. In the long run, being trendy and following current hype-cycles only makes the situation worse, and results in data management professionals losing respect.
The second approach is a persistent hype-cycle approach that attempts to make the current set of hype-cycles and terms a persistent data management profession. It attempts to establish the current state of hype-cycles and terminology as the persistent state for a formal data management profession. It avoids the long and circuitous route toward developing a formal data management profession.
The persistent hype-cycle approach is moderately difficult to achieve because most hype-cycles are not well-founded on sound concepts, principles, and techniques. Hype-cycles will eventually wane because they failed to provide the intended benefits, and will be replaced with new hype-cycles regardless of any attempt to make them persistent. The persistence is only temporary, will result in more effort to establish a formal data management profession, and the cost to organizations along the way will be tremendous.
The third approach is a transcend hype-cycle approach to establish a basic foundation for formal data management that transcends any past, current, or pending hype-cycles. It drives straight toward developing a formal data management profession based on sound theory, concepts, principles, and techniques. It establishes stability across change, avoids hype-cycles, and resolves the lexical challenge. It’s the best approach to achieve a persistent formal data management profession
The transcend hype-cycle approach is very difficult to achieve because it involves bucking current hype-cycles, personal agendas, and profit motives. It requires hard thought about establishing a formal set of concepts, principles, and techniques for managing data as a critical resource. It’s the least costly approach for organizations and it makes data management professionals look good in the long term. But, it’s the least popular approach in the short term and tends to be avoided.
The transcend hype-cycle approach is the best and only reasonable approach. It’s the approach that will achieve a formal data management profession in the shortest time at the least cost, and will gain the recognition and respect that is deserved.
The current status of a formal, certified, recognized, and respected data management profession is described below.
Formal means having a basic construct for managing data as a critical resource. That construct includes an established curriculum leading to a degree in data resource management, not a degree in information science or information technology. Such a curriculum does not exist.
Formal includes acceptable standards that promote managing data as a critical resource. Some standards do exist, but they are produced by a variety of different organizations, and are often incomplete, confusing, and conflicting. A complete set of formal, clear, non-conflicting data management standards must be developed within one overarching construct.
Formal includes professional publications where articles may be peer reviewed. Some good professional publications currently exist, but are largely about current hype-cycles and day-to-day physical processing details. Few are oriented toward formally managing data as a critical resource. The DAMA-DMBOK and DAMA Dictionary of Data Management are steps in the right direction, but are just a beginning.
Formal includes a prestigious professional organization that boldly leads the initiative to develop a formal data management profession. That organization must have a membership that represents a predominance of people in the data management profession.
Certified means that members of the profession are certified at different skill levels, such as novice, apprentice, journey, and master, and in different areas, such as analysis, design, implementation, and operation. Some progress has been made with certifications, but many different organizations are offering a variety of certifications that often overlap, conflict, or leave gaps. One overarching authority needs to be established for coordinating all data management certifications.
Recognized means that a data management profession, and data management professionals, is recognized by public and private sector organizations and by business professionals. Data management professionals have typically done a poor job at getting themselves properly recognized. Historically, they have created a lexical challenge, caused paralysis by analysis, developed brute force physical data bases, created and promoted hype-cycles, and produced massive quantities of disparate data. They have done more damage to themselves than anyone could have ever done to them. They have certainly earned recognition, but it has been the wrong kind of recognition.
Respected means gaining respect from peers, other professionals, and employers. Currently, data management professionals have minimum respect, and are doing little to gain respect. Like recognition, respect must be earned based on performance rather than demanded. Only data management professionals can earn the respect they deserve—no one else can earn respect for them.
Data management professionals may self-proclaim formal, it’s questionable if they can self-proclaim certified, and they certainly can’t self-proclaim recognized and respected. They must take the initiative and develop a formal data management profession. They must earn the right to be recognized and respected professionals. Data management professionals must work extra hard at developing a formal data management profession, cleaning up the disparity they have created, and properly managing data as a critical resource. They must stop demanding proper recognition and start earning proper recognition and respect.
The current status of a formal data management profession is analyzing the collection of disciplines and documenting those disciplines. The real progress of synthesizing a formal data management profession hasn’t begun. It’s coming, but it’s not here yet. The motto is If we don’t do it to ourselves, someone else will do it to us. So far neither has happened, but the time is coming. Data management professionals have the opportunity to choose working together to develop a formal data management profession.
What’s more likely to happen is that business professionals will step up to the task of creating a data management profession. It’s the business that’s scathing from poor data resource management. It’s the business professionals that have knowledge about the business and the data needed to support the business. It’s the business professionals that can learn the techniques and skills of managing data as a critical resource. Business professionals may well take over data resource management.
If a data management curriculum were established leading to a degree, the business professionals would likely be the majority registering, followed by the data management professionals. The business professionals have a profound interest, and ability, to manage data as a critical resource.
Developing a formal data management profession will have trials and tribulations. It will have successes and failures. It will have differences of opinions and intensive discussions. Some people will support the development and others will attempt to block the development. People will take action according to their own personal and financial agendas. Eventually, a formal data management profession will evolve and become firmly established. That’s the ultimate goal that needs to be achieved.
