5 common challenges facing data modelers today

I marvel at the speed at which technology is introduced and embraced in today’s world. As with most technical workers, it is both exciting and frightening. Understanding these technologies and keeping skills up-to-date to embrace them has always been a challenge to IT professionals.

Beyond this ever changing progression of technology are challenges just as daunting. Let’s take a look at five things that challenge me as a data modeler today.

  1. Staying relevant is more than being knowledgeable about BIG data, agile design, self-service BI or cloud computing. Relevancy as a data professional is greatly impacted by these technologies but is more about changes to self to work with these technologies. Time is everything today. Projects move fast and the life of an IT application gets shorter. Time necessitates that we become more responsive and deliver faster. Methods and deliverables from times past may still be relevant or not relevant. We are challenged to revisit them, assess their applicability and adapt them to be applicable. No doubt, we need to invest time in learning and integrating new methods and deliverables in our daily routines.
  2.  Juggling priorities is something we deal with daily in our home and work lives. Data modelers have worn many hats for years including analyst, modeler, facilitator and business systems analyst. We are sort of a jack of all trades and master of one: data modeling.The challenge that arises is the expectation that we can be the juggler extraordinaire. Today’s workplace reality is a decreased headcount with increased job responsibilities. As we know, 20% of your time on 5 projects does not equal 100% of your time. Multitasking with multiple priorities leads to stress and dissatisfaction if not properly addressed.
  3. Marketing ourselves, our profession and our value is a must. Data modelers are not marketers and possess personality traits that are generally not so sales like. It is nice to think that everyone understands what we do and values our contributions. I can personally attest that this is far from the truth. We offer great value and add to the bottom line. However, we have to get out there are let people know. Ever increasingly complex IT solutions has IT staffs struggling to understand the who, what, where, when and why of implementing a solution. We fare much better and are more effective when we proactively answer those questions for ourselves.
  4. Data is big and BIG. I have seen reports that data will burgeon by a factor of 44 by 2020, reaching a volume of 35.2 zettabytes . Now that is damn big. Data modelers stand on the forefront of data initiatives in the enterprise. That is intimidating. By now, you should be aware of BIG data and the technologies that boil it down to understandable facts and patterns that are key in business analytical decisions. Equally as daunting is understanding the data electronically hoarded over the past 50+ years. Data modelers are key in helping an ever increasing customer base transform this data into information.
  5. Our legacy can overshadow our actions. Data administration has changed over the years. That change is in the people, processes and technology. However, I have been dogged in many of my positions by acts from the past. A history of inflexible data modelers whose modeling efforts trudged on for months and years are not soon forgotten. Beyond the people issue, it is easy to be mired in piles of data models that may be out of date and inaccurate. Some data modeling efforts were dead ends where the model never materialized in a database or resembled the delivered product. A modeler’s reputation is based on how reliable and accurate their data modelers represent the enterprise.

I am presenting at Enterprise Data World 2014 in Austin, Texas.  I hope that you will join me in my session: And Other Duties as Assigned – Embracing New Roles to Grow in Your Enterprise. #EDW14

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