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21st Century Data Management Professions

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Data-oriented positions and professions may be less vulnerable to disruption by automation and new technologies, due to data management’s reliance on critical thinking, analysis, and human interaction

Introduction

No matter what job anyone has, the person has to know how to do that job. That is, after all, the reason the candidate was hired. Simple enough, right? Not really. The rapid growth and increasing diversity of data-related professions has transformed that into more than knowledge about a particular position. Over time, the focus has become knowledge about the profession as well as the skills required to perform the position. It is not enough to know the specific job. One must know about the profession and its direction, growth expectations, and developmental possibilities.

The data management community and related professions have gone from back office to center stage. The opportunities for data professionals are increasingly diverse, spanning numerous disciplines and business sectors. Success is possible for those who differentiate themselves through demonstrated understanding of their profession as a whole, along with developing progressively more valuable skills and knowledge, all within the framework of enterprise data management.

Professional Security

Many jobs and many fields are being replaced by robots and other forms of automation. Robots, robotic science, artificial intelligence have all moved from science fiction to science. Daily life offers the opportunity to interact with a machine instead of a human. ATMs instead of bank tellers. Siri / Ok Google / Alexa (voice controlled personal assistants). Self-checkout, or no check-out with Amazon Go, instead of cashiers. How rare is it to speak with a customer representative without first having a machine instruct to “press 1 to speak with a representative”? Digital arms races in the cyber world with AI-driven offenses and defenses and humans watching on the sidelines are not far off. Where have humans and their jobs gone? The tech sector has benefited from the change in employment, offering jobs in content management and programming. But not everyone wants a technology career and the world needs more than tech positions to exist and thrive.

An article in the NY Post cites 7 jobs robots cannot assume from a human. Based on an evaluation by journalist and author Reed Tucker of lifestyle trends along with requirements and desires of the working population, the list includes law enforcement (and related personal-service fields such as firefighting and physical therapists), health care and civil engineering. While robots and AI have a place in those professions, solving crimes, fighting fires, demands of caring for a growing aging population with increased longevity, building bridges and buildings all require human intelligence and intuition.

So does data analysis, one of the 7 professions on the list. With new layers of complications in the data analysis world such as privacy concerns, the Internet of Things and globalization, Tucker reports that data analysis is a job a robot can’t steal from a human and a profession with considerable growth potential. Intelligence and intuition have been and remain the foundations of data analysis career success. Knowledge and professional relationships bring dimension that robots cannot. Data analysis is about more than crunching numbers. It requires insight and judgment, a combination of art and science, and a focus on data management training.

Best Job in America

The career website Glassdoor named “data scientist” one of the best jobs in America, offering an exciting future for the data community. The Glassdoor ranking includes earnings potential, career opportunities and number of openings. High quality data is the foundation of successful businesses in numerous sectors. The data community combines art and science to produce positive results. The ability to aggregate, analyze, use and protect data is a mission-critical skill in finance, technology, retail, healthcare and insurance to name a few industries. While it might be tempting to resort to a crystal ball, data professionals realize and respect that science and data drive the process, and the art of analysis guides it.

Leverage Findings for Personal Growth

This all sounds great but it comes with a challenge. The increasing prominence and rapid growth of the data community and related professions requires that establish clear differentiators in professional development. Achievements beyond work accomplishments become increasingly important. Solid work experience must be complemented with continuing education and growth of a professional network. Individual growth not only contributes to the success of a career, it also contributes to the success of the organization. Many organizations do an outstanding job of supporting the growth of their teams. Regardless of what any organization is doing it up to the data professional to be proactive in their own professional development.

Advanced degrees are widely respected and recognized. The growth of the profession has brought the opportunity for flexible, targeted ways to learn. Seek them out and build knowledge and skills regularly. Mentoring, even in the early stages of a career, can help the both parties in the mentorship, providing an exchange of ideas and experiences that is unique. Likewise the exchange of ideas and experiences in a broader professional network brings dimension to knowledge and provides avenues for reaching beyond daily responsibilities.

Conclusion

In an always-changing workplace, basic professional knowledge is still fundamental, along with excellent job performance, done with focus and creativity. Go beyond those basics and fundamentals with investment in expanding basic skill sets and on continuing education. Aim for the differentiating factors in the rapidly growing and competitive community of data professionals. Always be knowledgeable about the profession in addition to specific job opportunities. Continually expand internal and external professional networks. Critical lessons and skills come not only from courses and books. They come from human interaction, exchange of ideas and learning from the paths others are taking in their careers.

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Aimee Siliato, FIDM

Aimee Siliato, FIDM is an experienced data management professional with related experience in actuarial science, product development and government relations. Aimee has led the Insurance Services Office’s, (a subsidiary of Verisk Analytics) data collection, acquisition and strategy department. She is a member of the Board of Directors and vice president of marketing for the Insurance Data Management Association (IDMA) and a past president and chair of the Board of Directors of IDMA. She is a contributing author to the textbook Introduction to Data Management Function and Tools. A graduate of Brooklyn College, Aimee obtained her fellowship in insurance data management in 2007.

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