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Data scientists have been the toast of organisations and they come at a premium. This scarcity poses a challenge for enterprises as they find it increasingly difficult to porch data scientists who are a difficult find and a goldmine to a business.
IT major IBM expects the demand for data scientists to increase by 28% by 2020 which is though a conservative figure. This will eventually give rise to a gap in demand and supply, making data scientists a rare find. To address this talent shortage, companies are investing into technologies that are as easy and drag and drop, democratising data science to effectively create citizen data scientists out of corporate employees who are not embedded in IT.
The idea behind the citizen data scientist trend lets organizations to leverage internal skills to bring the basic data science expertise in-house for advanced analytics while minimizing the burden on organizational resources. This shift brings Engineers into center stage having the ability to fill the role of citizen scientists, bringing their background in modeling, math and statistics into the table.
Citizen data scientists bring capabilities and practices which allow users to extract predictive and prescriptive insights from data while being on positions outside the field of statistics and analytics. Research firm Gartner adds that citizen data scientists are power users, including the business analysts who don't have computer science background but can perform simple to moderately analytical tasks with a little training.
Analytics providers are keen to build tools that support the citizen data scientist. These tools include data visualization tools, for data analysis and developing insights via drop and drag methods.
Data science tools are democratizing the low-end of data science, and powerful open source engines like Google TensorFlow and the deep learning libraries like MXNet, with Python and R programming languages are making the rise of Citizen Data Scientist even more prominent.
Many solution providers are addressing the democratization of data science by bringing more transparency and thus offsetting a change to democratise their data warehouses. Some are also embedding tools within their solutions geared for users who have experience with modeling and statistics, like engineers, but don't require data science math expertise. With the shift of analytics initiatives from pilot to becoming competencies within enterprise, the democratization of data science will increase in importance for the end user company.
Fortunately, becoming a citizen data scientist does not require a degree, or even a rigorous training. If you're interested to become a citizen data scientist, here are the steps that can help you to embrace your journey ahead.
1. Be inquisitive and ask for access to more data repositories.
It may happen that you get tired accessing the old data sources and get the citizen data scientist itch! If that happens, it may be the time to ask your supervisor for an additional access to data that is not included in your normal reports and data accessibility.
If data repositories are opened up in the favour of non-data scientists, the industry can see the strength and benefits that can be leveraged from citizen data science. IBM turned the 2016 Wimbledon tournament into a library of information by expanding data to a very unique group of citizen data scientists. IBM empowered tennis professionals to use their data analysis program, Watson Analytics for an unprecedented insight into players' performances.
2. Learn the use of Business Intelligence Software's.
After you get the access to new sources of data for new insights, it is important for you to know how to use the data friendly analytics tools for business intelligence. Features like advanced self-service data preparation, behavioural analytics, graph analytics, location analytics, web analytics and smart data discovery will help you inch one step closer to become the citizen data scientist who is the current toast of the technology world.
Advanced self-service data preparation has assisted Sears transform its business intelligence analysts into citizen data scientists. The giant has invested in Platfora's big data discovery software solution and has granted data access to 400 of their analysts. As a result, these analysts were able to deploy customer segmentation techniques to improve product recommendations for customers on the Sears website.
Learning to use advanced analytics offers a lot of benefits, depending on one's learning capabilities it may only take one to two weeks to get up to speed. In today's times, most vendors offer tutorials, community forums and training to meet the demand.
To add value and answer the demand calls, SAS has developed a unique curriculum tilled "Data Science for the Business User" to specifically address its training needs.
If you are willing to learn the new methods and deploy new tools regardless of whether or not you being a current SAS software user then you can join the SAS Citizen Data Scientist program.
To join this program, no prior SAS experience is a requisite. You just need to have a basic understanding of statistics and zeal to learn. SAS provides an access to online learning material prior to the course to help you get started.
Analytics is no longer the exclusive property of statisticians and specialists; it is becoming increasingly open-sourced and giving rise to Citizen Scientist trend; eager to gain an expertise and skills to add more value to the business organisation.
