According to research reports by Gartner, over 40% of data science related tasks will be automated by 2020, which will boost productivity and lead to wider use of data and analytics by Citizen Data Scientists. Gartner has also further predicted that Citizen Data Scientists would take over data scientists in terms of advanced analysis.

With fewer data scientists available within the organization, the skilled business or information analysts could take up the new role of Citizen Data Scientists. By providing them with the right tools, they can perform complex analysis for creating models that can make use of prescriptive or predictive analytics. As a result, enterprises can have access to greater data sources including complex types of data along with an increased range of capabilities in advanced analytics.

Let’s delve a bit deeper to understand how Citizen Data Scientists can bring about a drastic transformation among enterprises.

Who are Citizen Data Scientists and what has led to their emergence?

Gartner has defined Citizen Data Scientist as a person who builds or generates models that make use of advanced analytics or having prescriptive or predictive capabilities, but whose key function lies outside the area of analytics or statistics.

• The biggest challenge faced by companies around the world is the acute shortage of data scientists who can make effective use of big data and other advanced analytics tools. As a result, enterprises are adopting a forward-thinking approach to meet this growing demand for data scientists.
• Companies are recognizing key business talent or individuals who may not have specific training in statistics or mathematics but can provide meaningful and valuable insights on the business issues for the application of big data solutions.
• Further, these individuals are being trained to be specialists such that their core expertise lies in between the data scientists and the business users who will be known as the Citizen Data Scientists.

The Evolution of the Citizen Data Scientist

With the massive amounts of data being generated by companies, it has become necessary for company stakeholders to gain actionable intelligence regarding their companies and customers through available data. This has led to an increase in the demand for data scientists but there is limited availability of data scientists who can make sense of this data. The existing business analytics software tend to be monolithic and make only limited use of the data which could provide insights on past business metrics. There are significant gaps in technology, techniques, skills, and tools that employees use as organizations are not data smart although they are data rich.

However, in the last few years, business leaders started realizing the importance of using data to get meaningful insights or predictions about the future. There is a drastic shift in thinking among business leaders who want their employees to be able to take quick actions and use data as the basis for making key decisions. As a result, to fuel the shortage of supply of data scientists and encourage a greater number of highly skilled talent to be able to work with the data and solve business problems, there is a new role of a Citizen Data Scientist created to fill this increasing gap.

How can business users take up the role of Citizen Data Scientists?

Enterprises are now focusing on empowering core employees with data skills so that the task of data analysis can be taken up by them as every company may not be able to afford data scientists who are already scarce in number. Business users specifically may be the best fit to take up the role of Citizen Data Scientists and can become a valuable part of the data ecosystem as it evolves. The benefits are huge as it helps in the utilization of intelligent resources who may be able to work with real business and industry experience.

For example – Sears, a US-based company, made a massive investment in its citizen data program by empowering 400 staff members through its Business Intelligence operations to do advanced and big data-based customer segmentation. This task was carried out earlier by Big data analysts within the company, and by taking this huge step, Sears was able to have hundreds and thousands of dollars’ worth of efficiencies through data preparation costs.

Today’s latest technologies such as AI can offer insights from advanced analytics to business users or Citizen Data Scientists, without the need for them to have any traditional expertise required by data scientists. AI can empower average business users to get over the complexities of the algorithms by automatically figuring out the findings and perspectives that matter most to their business.

Key Characteristics of Citizen Data Scientist

Citizen data scientists may be from various departments within an enterprise with hundreds and thousands of employees. However, not all individuals may necessarily have the required skills to take up this vital role. There are some core traits which employees or business users need to have to qualify as the right candidate for this role which is discussed below:

Choosing the right person with the best skills

Citizen data scientists from key functional areas of business such as finance, sales, operations or customer support can be more effective as they have a better understanding of specific challenges faced in these areas. Besides, they are able to take logical decisions based on the circumstances rather than on gut-feelings and can perform better.

Build cross-functional relationships

They must be able to work with different types of individuals, accommodate their working styles, and communicative effectively within different settings. They need to have an affinity towards information systems with patience, good communication, and a solid grasp of the competitive business requirements and constraints of the IT infrastructure among other key qualities.

Must have experience dealing with data

They need to have experience of meeting the challenges of accessing and preparing the data which may be required. Besides, these individuals must be able to set objectives, form hypotheses, and ask questions based on them. It is also helpful to find someone who is inquisitive by nature, likes to experiment, and is innovate using new tools.

Conclusion

The new age Citizen Data Scientists may be provided with sophisticated tools within an easy to use environment to get better clarity, accuracy in data, reports and enhance the overall effectiveness of the decision-making process within the organization.