Data scientists have become every industry’s must-have hire. Their ability to extract and understand data and trends has made their skills a highly sort after commodity. After all, the information they gather is key to decisions about business intelligence.
About the author
Jens Krueger, Chief Technology Officer, EMEA at Workday.
However, the high demand for data scientists can make them prohibitively expensive for midsize companies. To fill this void, citizen data scientists present an effective, affordable, long-term solution and can be trained in-house as soon as the need for them is identified. This is key to unlocking insights in data, that can be used to make better business decisions, which will ultimately improve the company’s competitive posture.
What are citizen data scientists?
Businesses do not have to look far to find citizen data scientists, they are already in their midst in the form of existing staff. A citizen data scientist is an employee who has a natural interest in data and analytics and is capable of performing simple to moderately sophisticated analytical tasks using automated, business intelligence (BI) solutions.
These individuals are unlikely to have the coding skills possessed by those with formal data science training, but will be capable of using BI tools to gather actionable insights from data. Midsize companies can easily develop these citizen data scientists by identifying those with minimal skills and providing them with training to advance their analytical mindsets.
How can businesses cultivate citizen data scientists?
Cultivating citizen data scientists relies on recognizing specific skills and nurturing them. The first step in achieving this is identifying employees in both IT and business roles who have existing analytical experience, or the passion and potential to develop the capabilities. They then need to be brought together to receive basic data science training. Once this has been done, they will be able to become active players in their companies’ efforts to tap into the value of big data and use it to drive business transformation, innovation and growth.
After an initial group has been established and trained they must then be encouraged to share their expertise and learning and come together to develop new ideas. This will advance their collective data science skills and create a culture of innovation and collaboration across the business. All with minimal lift from leadership or independent experts.
Broadening this network to other colleagues will also be key to socializing their insights beyond the initial group and fostering an insight-led decision making culture. This can be achieved by encouraging citizen data scientists to apply their business intelligence learnings outside of their departments, and become mentors for other colleagues who show an aptitude for the role.
Technology’s role in fuelling the rise of citizen data scientists
It would be impossible for employees to become citizen data scientists without technology empowering them to perform complex tasks. Previously, insight could not be derived until the data had been manually prepared. This required advanced statistical and analytical skills that are beyond the citizen data scientist. However, augmented analytics has made data science more accessible.
Machine learning and artificial intelligence (AI) now remove the heavy lifting from data preparation and insight extraction, enabling more staff to explore and analyse data in business intelligence and analytics platforms.
How technology and data science work together in practice
Now that we have intelligent technology in place, data analysis no longer means weeks of gathering and reconciling data. Cloud-based analytics tools have accelerated the data-crunching process to a matter of seconds. This ensures business and finance leaders are always able to make well-informed choices with the backing of quantitative data.
Imagine you are a leading midsize company and your latest income statements indicate that the business is on course to meet its year-end revenue goals. However, this is not yet guaranteed, so you need to take steps to ensure momentum continues. Using business intelligence tools, founded on augmented analytics, citizen data scientists can quickly and easily streamline and analyse disparate sets of data.
This allows them to approach data with strategic curiosity and move beyond basic questions such as what their current revenue booked for the quarter is. Instead, they can make nuanced inquiries into why their sales pipeline might look significantly different across regions or why newer sales people appear to be performing better than their more experienced counterparts. Armed with these answers, business leaders will have the insight required to make improved business decisions. What’s more, this can be done at speed, with just a few clicks.
Citizen data scientists are the future
Traditionally, gathering insights from data required formal data science training, a requirement that has become more important as the volume of data has steadily increased over the past five years. However, midsize companies can now circumvent the skills gap, and reap the benefits of data analysis, by embracing new technology and identifying and upskilling citizen data scientists.
These individuals demonstrate that anyone with analytical capabilities can become champions for data-driven decision making. This upskilling is ultimately the key to driving data-backed business innovation which will improve the companies’ competitive stance.
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About the author
Jens Krueger, Chief Technology Officer, EMEA at Workday.
However, the high demand for data scientists can make them prohibitively expensive for midsize companies. To fill this void, citizen data scientists present an effective, affordable, long-term solution and can be trained in-house as soon as the need for them is identified. This is key to unlocking insights in data, that can be used to make better business decisions, which will ultimately improve the company’s competitive posture.
What are citizen data scientists?
Businesses do not have to look far to find citizen data scientists, they are already in their midst in the form of existing staff. A citizen data scientist is an employee who has a natural interest in data and analytics and is capable of performing simple to moderately sophisticated analytical tasks using automated, business intelligence (BI) solutions.
These individuals are unlikely to have the coding skills possessed by those with formal data science training, but will be capable of using BI tools to gather actionable insights from data. Midsize companies can easily develop these citizen data scientists by identifying those with minimal skills and providing them with training to advance their analytical mindsets.
How can businesses cultivate citizen data scientists?
Cultivating citizen data scientists relies on recognizing specific skills and nurturing them. The first step in achieving this is identifying employees in both IT and business roles who have existing analytical experience, or the passion and potential to develop the capabilities. They then need to be brought together to receive basic data science training. Once this has been done, they will be able to become active players in their companies’ efforts to tap into the value of big data and use it to drive business transformation, innovation and growth.
After an initial group has been established and trained they must then be encouraged to share their expertise and learning and come together to develop new ideas. This will advance their collective data science skills and create a culture of innovation and collaboration across the business. All with minimal lift from leadership or independent experts.
Broadening this network to other colleagues will also be key to socializing their insights beyond the initial group and fostering an insight-led decision making culture. This can be achieved by encouraging citizen data scientists to apply their business intelligence learnings outside of their departments, and become mentors for other colleagues who show an aptitude for the role.
Technology’s role in fuelling the rise of citizen data scientists
It would be impossible for employees to become citizen data scientists without technology empowering them to perform complex tasks. Previously, insight could not be derived until the data had been manually prepared. This required advanced statistical and analytical skills that are beyond the citizen data scientist. However, augmented analytics has made data science more accessible.
Machine learning and artificial intelligence (AI) now remove the heavy lifting from data preparation and insight extraction, enabling more staff to explore and analyse data in business intelligence and analytics platforms.
How technology and data science work together in practice
Now that we have intelligent technology in place, data analysis no longer means weeks of gathering and reconciling data. Cloud-based analytics tools have accelerated the data-crunching process to a matter of seconds. This ensures business and finance leaders are always able to make well-informed choices with the backing of quantitative data.
Imagine you are a leading midsize company and your latest income statements indicate that the business is on course to meet its year-end revenue goals. However, this is not yet guaranteed, so you need to take steps to ensure momentum continues. Using business intelligence tools, founded on augmented analytics, citizen data scientists can quickly and easily streamline and analyse disparate sets of data.
This allows them to approach data with strategic curiosity and move beyond basic questions such as what their current revenue booked for the quarter is. Instead, they can make nuanced inquiries into why their sales pipeline might look significantly different across regions or why newer sales people appear to be performing better than their more experienced counterparts. Armed with these answers, business leaders will have the insight required to make improved business decisions. What’s more, this can be done at speed, with just a few clicks.
Citizen data scientists are the future
Traditionally, gathering insights from data required formal data science training, a requirement that has become more important as the volume of data has steadily increased over the past five years. However, midsize companies can now circumvent the skills gap, and reap the benefits of data analysis, by embracing new technology and identifying and upskilling citizen data scientists.
These individuals demonstrate that anyone with analytical capabilities can become champions for data-driven decision making. This upskilling is ultimately the key to driving data-backed business innovation which will improve the companies’ competitive stance.
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