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Citizen Data Scientists Can Use Assisted Predictive Modeling to Create, Share and Collaborate
Citizen Data Scientists Can Use Assisted Predictive Modeling to Create, Share and Collaborate

June 23, 2023

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Gartner has predicted that, ‘40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’

If you are a Citizen Data Scientist candidate or you are already working within the ranks of the Citizen Data Scientist community, you know that analytics can be helpful in streamlining your work process, gaining insight into crucial issues that inform the success or failure of a task or product, and collaborating with and sharing data with other business users to achieve better results.

Anyone who has worked in a business, an association or a community of professionals knows that leveraging the experience and skills of a group will always result in a better outcome and, when you combine those skills with clear, concise data, the team can make the best decisions, using the most recent, most complete information.

In this article, we discuss some of the benefits of assisted predictive modeling, and how it can help the organization and Citizen Data Scientist candidates to optimize resources and knowledge and achieve results.

‘When assisted predictive modeling is used to inform and support the planning and forecasting process, the organization can achieve more dependable results, and it can validate the value of the Citizen Data Scientist approach to data analytics.’

Assisted predictive modeling employs sophisticated analytical and forecasting techniques and presents information in a self-serve environment so business users with average skills can utilize these techniques without a data science background. Users can produce and share reports without the assistance of IT team members or analysts.

 

Assisted predictive modeling leverages historical data and other elements to predict and forecast outcomes. It uses machine learning to provide the user with the best fit so that they can use the algorithm that is the most suitable for the data they want to analyze, so users can explore patterns in the data and receive auto-suggestions and information that will provide insight – all without complex data manipulation or in-depth knowledge of applicable algorithms and techniques.

 

Benefits:

  • No complex algorithms or data manipulation
  • Auto-recommendations for underlying data with no advanced skills required
  • Analyze, share and optimize business potential
  • Prototype and hypothesize without professional assistance
  • Encourage user adoption

 

When a user engages with the assisted predictive modeling tool, they simply select a dataset and perform analytics. They can then refine the analytics, make different choices, and share with other users, so theories and hypotheses can be improved and analyzed until the team a) has gained the insight they need and, b) can make a fact-based decision.

Power users can create and share models to elevate the skills and knowledge of the team, and ensure that everyone is working with the right information. The team can share the models and, in so doing, learn from the process.

As the Citizen Data Scientist community evolves within your organization, these models will become the foundation for data democratization, improved data literacy and shared data popularity.

When assisted predictive modeling is used to inform and support the planning and forecasting process, the organization can achieve more dependable results, and it can validate the value of the Citizen Data Scientist approach to data analytics.

Because this process is collaborative, it allows the enterprise to transition its culture by leveraging power users and those who are curious about data analytics and allowing them to share models and information with other team members, building a more collaborative team environment and supporting the evolution of the Citizen Data Scientist initiative across the enterprise.

‘Assisted predictive modeling leverages sophisticated analytical and forecasting techniques and presents information in a self-serve environment so business users with average skills can utilize these techniques.’

When an organization implements a Citizen Data Scientist initiative, it can leverage Assisted Predictive Modeling and provide advantages to the organization, to the business users and to data scientists, and it can provide numerous benefits to you as a Citizen Data Scientist candidate.


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KartikPatel

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