AI & ML Fintech

Asking The Right Question: The Key To Data Disruption And The Convergence Of Data Science Personas (Dean Stoecker,

Today’s businesses are reconciling a dizzying amount of disparate data, forcing leaders to strategize on how to make sense of the surplus of information in front of them. Eager to transform a sea of data into actionable insights, executives often look to data scientists to lead the way. However, therein lies the problem—there are not enough data scientists available to solve the multitude of problems that businesses face. Data is simply getting ahead of the number of PhDs out there, which means operationalizing it can no longer be the responsibility of one role or one department alone.

However, solving this issue isn’t entirely contingent on solving the skills gap as a whole. In fact, this problem can be assuaged by engaging both data scientists and citizen data scientists for help in addressing the influx of information and more importantly, working to converge those two personas together. Here’s why:

Businessman raising hand to ask question in seminar
Rear view shot of a businessman raising hand to ask a question. GETTY

Capture Missed Opportunities

As new sources of data surface and data-capture rapidly expand in enterprise software, businesses are inundated with information. There is a crucial imbalance of supply and demand; demand for answers outstripping the supply of people—or perceived supply of people—capable of delivering them. This imbalance leaves complex questions unanswered, talent overlooked and money on the table as businesses face the daunting task of surviving today’s shrinking half-life.

The impact of this missed opportunity is profound; The State of Dark Data report published by Splunk found that 55 percent of organizations’ data is dark and yet, business and IT leaders across the globe agree that data is critical to success. We are past recognizing the tremendous potential for data, but the challenge is turning that data into actionable insights to improve business results and understanding how to leverage existing talent to do it. Analytic maturity is quickly transitioning from a nice-to-have to a critical business imperative and a key indicator for the future of the company—without it, business profitability and even viability will falter. As for the organizations that have it figured it out… they’re likely responsible for the convergence of the data scientist and citizen data scientist personas witnessed in the market.Today In: Innovation

Converge and Conquer

It’s one thing to engage both data scientists and citizen data scientists to tackle Big Data, it’s another entirely to empower them to work together in an effective and meaningful way. For starters, that means ensuring both personas feel supported to tackle the tasks that make sense for their specific strengths and goals. Data scientists want to leverage their superpowers and advanced skills to work on unique edge cases, but in order to do so, they need to delegate lower-level analysis to citizen data scientists. Achieving this requires businesses to empower citizen data scientists to take on tasks that have been put on a pedestal but are, in reality, very achievable. For example, building predictive models is a task often reserved for data science teams and yet, building the model is not a challenging task in and of itself—the challenge is understanding what question to ask. And therein lies an opportunity to reframe how talent is leveraged and to invoke an innate human curiosity among every data worker in an organization.


By working in tandem with one another, data scientists and citizen data scientists can highlight meaningful next steps in a quick and effective manner and organizations can capitalize on untapped talent waiting to accelerate the path to analytic maturity. Organizations that can recognize and capture this opportunity will outpace competition, advance innovation, up-level business strategy and ultimately, will monetize the value locked in dark data.  

Business team discusses analytic insights to inform decisions.
Business team discusses analytic insights to inform decisions. GETTY

Progress via Untapped Potential

While bridging the talent gap is no trivial task and data scientists remain in limited supply, solving for the insurgence of data is a realistic achievement when organizations assign responsibility beyond one role or one department, empowering all data workers to ask the right questions. By activating the untapped potential of citizen data scientists and pairing it in a way that compliments the work of data scientists, organizations will soon find a competitive advantage within the influx of data. The key success factor to this convergence? Empowering data workers with the right tools and technology for success, as fueling the convergence of personas is contingent on fostering the convergence of human and the machine.

Dean Stoecker

Dean Stoecker

Dean Stoecker is the founder, chairman and chief executive officer (CEO) of Alteryx. Dean’s leadership and motivational skills, along with his ability to create, communicate, and realize a vision, are a driving force behind the company’s 20 year success. Dean serves as an advisor to entrepreneurs and is an active philanthropist, creating the Alteryx for Good program to bring the thrill of solving real-world problems to nonprofits, educators, and local communities. Dean is passionate about humanizing the world of data science and analytics, evident in the company’s efforts to influence social change.

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