Data-driven change has impacted almost every area of business, making the work of Citizen Data Scientists increasingly important to business leaders. According to Gartner, the definition of a Citizen Data Scientist is: “An individual who builds or produces models using advanced diagnostic analytics or predictive and prescriptive capabilities, but whose primary work is outside the realm of statistics and analytics.”
Overall data collection has multiplied in recent years and will double again in the next two years. The new limiting factor in data analysis will be human resources. By making a deep pool of clean, modelled data accessible to more experts, an organization can pave the way for Citizen Data Scientists to succeed and grow its internal analytical resources.
Creating a Data-driven Culture
Though processes and technology are important to empower a Citizen Data Scientist, it is also vital to foster a data-driven culture within the organization. This will help open up the work of Citizen Data Scientists to more people and increase their recognition and ability to effect change among employees. In addition, Citizen Data Scientists need the support of leaders in the early stages of digital transformation. Citizen Data Scientists act as change agents who need to gain the consensus of employees across the organization. They can’t do it alone.
Add skills that enable Augmented Analytics
Gartner says organizations should consider incrementally adding capabilities that expand the scope of analytics tools that are used effectively, rather than taking a “big-picture” approach. This means that data and analytics leaders should provide extensions to Citizen Data Scientists’ existing tools rather than overwhelming them with entirely new tools.
Augmented analytics offers a targeted and intelligent way to address some of the key stages, for example, augmented data preparation, augmented data discovery and augmented data science. Data and analytics leaders can add them to the existing Citizen Data Scientists toolkit.
Robust data and Analytics Governance
Without the right governance processes in place, citizen data scientists will not be able to realize their potential. While there is no doubt that a Citizen Data Scientist is incredible, it is equally important to know that the Citizen Data Scientist should be treated with a data governance framework that recognizes data ownership, assesses tasks, trains data literacy, refines queries, highlights unused reports and dashboards and provides other data governance and management activities.
Collaboration Channels between Citizen Data Scientists and Expert Data Scientists
According to Gartner, Citizen Data Scientists cannot replace Expert Data Scientists but are a complement to existing analyst jobs. Citizen Data Scientists should not use self-service data science platforms silently. In all cases, they should participate in the development process together with the Data Scientist, who is ultimately responsible for approving models before they go into production.
The right tools and the right training
To unlock the business benefits of data analytics, innovation must be made accessible to more people. Today’s analytics and business intelligence tools allow companies to make huge strides in less time. Combined with the right training and education.
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