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Why Should Business Users WANT to be a Citizen Data Scientist?
Why Should Business Users WANT to be a Citizen Data Scientist?

November 14, 2024

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When a business decides to undertake a data democratization initiative, improve data literacy and create a role for Citizen Data Scientists, the management team often assumes that business users will be eager to participate, and that assumption can cause these initiatives to fail.

Like every other cultural shift within an organization, the management team must support the transition to Citizen Data Scientists by educating team members and helping them to understand the benefits of these changes.

‘To convince business users that the Citizen Data Scientist role offers career opportunities and can make daily tasks and activities easier for all team members, the organization must ensure that business users can see and experience the real value of augmented analytics tools.’

The world-renowned technology research firm, Gartner, has published reams of research on the Citizen Data Scientist phenomenon. Here are just two of their many strategic predictions.

  •  '...the number of citizen data scientists will grow five times faster than the number of expert data scientists.'
  •  '...citizen data scientists will surpass data scientists in the amount of advanced analysis produced.'

While that perspective bodes well for the enterprise, it does nothing to convince business users that this change will be good for them. Team members often see this type of change as adding to their workload, or burdening them with additional responsibilities and that can mean they will be resistant to exploring the benefits and advantages.

First, business users must understand the role of a Citizen Data Scientist. This role includes:

  • The use of self-serve, easy-to-use augmented analytics tools to hypothesize, prototype, analyze and forecast results to avoid rework and costly missteps
  • Using domain, industry and primary skills and expertise to review and gain insight into data for better decisions
  • Interaction with data scientists and/or IT to establish use cases and refine outcomes across the enterprise
  • Sharing data and models with other users
  • Leveraging accurate, timely data and metrics to make recommendations
  • Improving time to market and time to decision and approval processes

In order to convince business users that this role offers career opportunities and can make daily tasks and activities easier, the organization must ensure that they can see and experience the real value of augmented analytics tools and how these tools can help them do their job more efficiently, more quickly and with better outcomes. The enterprise should present a strong case for this cultural and organizational change, including:

  • How business users will interact with Augmented Analytics solutions
  • How the information they gather and analyze can help them do their job
  • How this new insight into data analytics can support career goals and provide visibility for advancement
  • How real world use cases can reveal the benefits of analytics
  • How business users can explore the role using free Citizen Data Scientist online educational tools

‘Like every other cultural shift within an organization, the management team must support the transition to Citizen Data Scientists by educating team members and helping them to understand the benefits of these changes.’

Business users who are interested in becoming a Citizen Data Scientist must be willing to embrace new technology and tools and work at the leading edge of a new approach to collaboration and decision-making.

 


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KartikPatel

Comment

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The concept of "Citizen Data Scientists" is transformative for businesses, offering an accessible entry into data science for non-technical users. However, the challenge lies in making these tools intuitive and convincing business users of the real value, from faster decision-making to career advancement. The shift requires leadership support, clear use cases, and hands-on training to drive adoption and maximize the potential of augmented analytics in everyday tasks.

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