Insights from Insight: Who is a citizen data scientist?
In this podcast from IBM Insight 2015, big data evangelist James Kobielus asks a panel of social experts the question that set Insight abuzz: Who is a citizen data scientist?
The panel comprised the following social VIPs:
- Lillian Pierson: Speaker, author, trainer and consultant specializing in data science, analytics and big data
- Mike Tamir: Data scientist and teacher focusing on machine learning; chief science officer with Galvanize
- Andrew C. Oliver: Founder and president of Mammoth Data, Inc.
- Matt Ridings: Entrepreneur, business and marketing strategist and frequent keynote speaker; former CEO of SideraWorks
- Bob Hayes: Chief research officer at AnalyticsWeek
Given only 60 seconds to produce a definition of a citizen data scientist, each member of the panel offered a distinct spin on the term. Each agreed that the data generated by everyday citizens is becoming part of the data paradigm and that analysis of that data is driving larger action.
One respondent cited the social messaging that attended the onset of Hurricane Patricia. Capturing analyzing data from tweets during the life of the hurricane allowed authorities to direct an informed response to the natural disaster and provided a noteworthy example of citizens generating data for the public good.
A few respondents held that citizen data scientists are those who can serve themselves, relying on the latest technologies and tools to answer their own questions without blindly relying on IT personnel. Such citizens have been empowered to use technology and tools to find answers to the questions that drive them.
However, each panel participant agreed on one important point: As nontraditional data scientists enter the field, data science is becoming more democratized by the day.
To explore the role of citizen data scientists in the cognitive era, listen to the podcast, then read more on our blog.
Also, for an in-depth look at how Spark has become a tool of the new breed of citizen data scientists, check out this informative IBM Analytics resource page.