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Cultivate Tomorrow's Citizen Data Scientists

In preparing for an inquiry with an industry analyst this week, I spent some time reviewing what analysts and other pundits have to say about the role of the so-called citizen data scientist. What I determined is that opinions are split. Some believe this role is instrumental to take machine learning and data science out of the ivory tower and into day-to-day operations of the business. Others challenge whether this role really exists—more of a data scientist in sheep's clothing.

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No matter where you come down on the issue, there's no denying that machine learning, and data science is moving ever closer to mainline analytics and business intelligence, and workers of all stripes must become conversant, even active participants, in understanding what it means, where it can influence how you work, and how people will interact with it.

Getting Started

Machine learning can seem like a very technical and intimidating topic. So, let's break it down—first by setting the tone.

"Lies, damned lies, and statistics…"

No one really knows where this quote came from, but it's a good one.  If you've taken advanced stats courses, your own personal quote might be much stronger than that. You can use numbers to tell many stories, but unless you understand the subject matter and the data, how it's been prepared, and how it's being used, you can easily be led astray.

Understanding your business and your data and how it's collected, where it's incomplete, why it's less than pristine, is key to framing how machine learning can influence what you take away from the data.

Necessary Skills

In a recent Gartner report—Maximize the Value of Your Data Science Efforts by Empowering Citizen Data Scientists—by Carlie Idoine and Erick Brethenoux, they rank six skills needed to be a successful citizen data scientist. The two "strong skills" needed are business acumen and "soft skills." Soft skills include things like communication, problem solving, and interpersonal skills, etc. and are often the secret sauce that define success in these types of roles. 

According to Gartner, the only roles that require strong soft skills are data scientist and business analyst. So, it's logical to say that best source of tomorrow's citizen data scientists will come from the business analyst community.

Right Training

So, do you see data science in your future? There are three things I would suggest you consider.

  1. See what augmented analytics capabilities are available to you.  Check out this video below to show how artificial intelligence (AI) driven by machine learning can be easily invoked—explaining attributes and measure, forecasting trends, identifying outliers and clusters, etc.  These are driven by algorithms that don't require any more than point and click.



  1. Participate in online training. Oracle offers a free course on Udemy.com that nicely addresses the ins and outs of algorithms, what they're for, and how they work.
  2. Find coursework at your local university or through online learning sites such as Coursera. A few years ago, I took an intensive statistics and predictive analytics course online from Columbia University, and it added another level of depth to my understanding of these topics. Many universities also offer certificates and advanced degrees in analytics and data science that may be in your future. Your employer may also offer training, so look there too. 


Like it or not, machine learning, and data science are now part of the fabric of your business. Regardless of your role or where you see your future, getting familiar with these topics is something you should put in your 2020 skills development plan.

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Comments ( 2 )
  • Charlie Berger Thursday, February 6, 2020
    Totally agree! Check out this related "The Changing Role of the DBA; From Database Developer to Data Scientist in 6 Weeks!" on-demand webinar.
  • Tony Cassidy Thursday, February 20, 2020
    Encountering the customer experience around transition from Business Analyst to Citizen Data Scientist more and more... often made easy to understand by mapping out the Security and User Roles and Responsibilities...it’s a very positive transition for most ✅
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