
In today’s data-driven workplace, data professionals face a constant challenge: validating their expertise while maintaining day-to-day responsibilities. One solution increasingly lies in attaining professional certification, a formalized training framework that provides practical experience.
Some industry professionals may believe that learning on the job and a track record of successful projects provide equivalent evidence of expertise to formal certification. However, this view overlooks the measurable return on investment (ROI) that certification programs offer for career advancement and salary potential.
This value becomes clear when researched. DATAVERSITY’s 2024 “Trends in Data Management” survey noted that the number of data professionals without off-the-job training decreased by 7% since 2023. With the highly technical nature of data management and the significant risks associated with errors, especially given the rise of regulations, this decrease in the learn-by-doing approach makes sense.
As organizations turn to those with more formal training, especially in data governance, they increasingly emphasize validated expertise. Consequently, more data professionals are turning to certification options to become specialists. We asked Mark Horseman, data evangelist at DATAVERSITY, to share his insights on getting certified as a data professional.
What Is Certification and Why Should Data Professionals Care?
Certification goes beyond theoretical knowledge. It gives practitioners a structured framework of proven practices to put to use in real-world situations. As Horseman explains:
“A certification represents a guided path to not only learn a specialist topic, like data governance, but to apply it as well.”
He emphasizes that certification demonstrates more than credentials. It shows that an individual can execute and apply knowledge to address critical business needs.
As employers see the benefits of certified individuals, they become more demanding of trained talent. Organizations want to “have a team of skilled individuals to help the business succeed,” he says. With validated proof of practical expertise from their workforce, companies demonstrate dedication to training and recognition for those who are certified, as having the necessary skills and abilities to carry out their tasks.
Key Certification Benefits
Beyond validating expertise, certification delivers three distinct professional benefits.
- Career advancement: Recently, Horseman attained a Certified Data Management Professional (CDMP) designation at the master level. This certification enables him to teach Data Management Body of Knowledge (DMBoK) content and has led to increased speaking opportunities at industry conferences.
- Standardized implementation skills: When a professional gets credentialed, they learn best practices for building data governance programs and implementing various data management components. This expertise “prevents cutting corners” and allows businesses to spend resources wisely, Horseman says, to achieve business goals.
- Organizational impact: As employers adopt newer and more efficient methodologies, they need knowledgeable people to execute them. For example, at a recent organization, specific business units needed specialized project management capabilities, known as Scrum. Horseman trained and received certification as a Scrum Master, and became a much-needed lead for a team there.
While certifying capabilities brings many wins among data professionals and industries, its relevance depends upon the training obtained and organizational requirements.
Making the Decision to Get Certified
Before pursuing professional credentials, data professionals must carefully consider the end results they want. Will spending the time and money lead to increased profitability and advancement in work roles? Deciding yes or no involves evaluating three key factors:
- Current expertise: Horseman cautions against jumping into multiple training programs back to back: “Give yourself a bit of a break before getting a ‘next’ certification.” Gaining professional experience also opens an understanding of what clients and employers need.
- Organizational needs: What are the organizational culture and team requirements? Some places emphasize a leadership role and prize specific data literacy capabilities. One company may want a strong understanding of data governance frameworks and methodologies, and another expertise in privacy and regulatory frameworks.
- Career trajectory: Professionals and organizations want to be known as gurus in certain areas. For example, Horseman focused on data governance and data quality to “communicate to the world he had specific expert knowledge in these.”
Once professionals have evaluated these key factors and decided to pursue certification, the next step is selecting the right program. Brand recognition, according to Horseman, plays a crucial role in this decision. “Ultimately, a certification is most valuable when the granting organization is highly reputable,” he explains.
Choosing the Right Certification Program
Should a data professional decide to pursue certification, they need programs for a good fit. Training that offers brand recognition should be highly considered. Additionally, Horseman suggests assessing three other factors:
- Relevance: Look for certifications that teach practical implementation skills. For example, if someone wants to lead data governance at a company, that training needs to demonstrate best practices and actionable steps. That way, the certified professional can spearhead the data governance initiative.
- Industry recognition: Some organizations partner with an educational provider to offer training. For example, Beck’s Hybrids implemented an educational platform to effectively communicate and deliver data literacy classes to their workers. Horseman says that this type of organization “shows leadership and dedication to the development of its staff.”
- Professional community engagement: Consider the opportunities to network and share knowledge at events, like conferences. He notes:
“Certification connects a community of professionals that share in the experience. When you see another person has achieved the same credentials, you have an instant kinship.”
Once you’ve identified a certification program that meets all the key criteria – brand recognition, practical relevance, industry backing, and networking potential – it’s time to act. To apply, a professional can register for a comprehensive exam or take a structured series of courses. While the details differ, best practices among different programs remain similar.
Best Practices to Get Started
When starting a certification program, professionals want to make the most of their learning and efforts. Horseman suggests these three best practices:
- Set up a study schedule: Many certifications can be completed through self-study and self-start. “Set aside dedicated time each week for studying and reviewing content,” says Horseman. Consistent engagement with small chunks of the learning material will lead to more success than trying to cram everything in a 24-hour period.
- Consider an institution or certified trainer: Be honest about potential delays with self-study. Some people learn best in a rigorous program, and this provides a great way to network too. He advised professionals to consider formalized training “offered by an institution or certified trainer.”
- Stay up to date on industry trends and tools: Horseman sees that the data profession evolves quickly. So, tap the certification provider for good resources with articles or podcasts that uncover the latest trends and emerging tools and techniques. Use this information to supplement training as a data professional and open career opportunities.
With the completion of certification and professional insights, professionals gain needed expertise. Additionally, certified professionals can share this knowledge with their teammates, passing on good practices to others in the workplace.
Conclusion
As businesses increasingly become data-driven and technology evolves rapidly, the ROI for professional certification becomes increasingly clear. For example, interest in data governance has risen from 60% of organizations in 2023 to 71% in 2024, leading organizations to demand expertise in this area.
With this kind of expectation, professionals must immediately fill in skill gaps and reduce troubleshooting time. Mark Horseman asserts that a professional with the relevant certification has the necessary skills and abilities to meet these corporate requirements.
However, the decision to pursue certification requires careful evaluation of how it will meet professional and organizational goals. Once committed to training, data professionals must research providers to choose the right program. Success then depends on establishing a regular study schedule, staying current with data management trends, and building connections within the professional community.
Companies benefit as data professionals learn and adopt new, efficient methodologies. This structured approach helps organizations avoid common pitfalls while maximizing the value of their data assets. Ultimately, getting certified allows both professionals and their organizations to position themselves at the forefront of data-driven innovation.