How to transform business users into data scientists
What if I told you that in just a few clicks, an ordinary business software user could transform into a data scientist? As far-fetched as this scenario sounds, this capability is more within reach than you may believe.
New business intelligence solutions have created the role of what we now dub the “citizen data scientist”. This group of professionals is inclusive of business professionals without development skills that still hold the ability to apply data intelligence insights to business strategy.
The growing demand for data automation
The growing amount of amassed data in organizations is a big driver in the trend of automation. In fact, Gartner analysts suggested in 2017, 40% of data science tasks could be automated by 2020.
Now in 2019, we can see that automating the tasks of data scientists did not undermine their importance but rather paved the way for them to become more productive. Just as well, business users are now able to access and use business intelligence software that was formerly designed for more technical employees
In recent insights from Deloitte, they share their take on the demand for automation in the data science space:
“By some estimates, data scientists spend around 80 percent of their time on repetitive and tedious tasks that can be fully or partially automated. These tasks might include data preparation, feature engineering and selection, and algorithm selection and evaluation.”
While some software providers have oversimplified BI solutions and others have created solutions too complex for the average business user to interact with, there are still highly effective BI solutions that strike a good balance between both ends of the spectrum.
When searching for an effective BI solution for business users and data scientists, research shows the key lies in a user-friendly UX. Essentially an interface that empowers data novices to make use of the software within the bounds of their present skill sets. User-friendly solutions like these are important because they help teams breakdown the complexity of technical language barriers by anticipating the needs of business users.
From visual dashboards to report builders, powerful BI solutions are dominating the tech space with easy-to-use UX and quick execution.
What’s driving the convergence of technical and non-technical users?
For more than a few decades, we’ve seen organizations bridging the gap between business users and their IT departments with little success. That was until the emergence of low-code business software has shifted this dynamic.
With the emergence of low-code software came the ability for non-technical users to address business challenges without consistently relying on technical users for data. As these solutions proved their worth, it made way for more platforms to emphasize user-friendly template builders, automated data forms and reporting, and visual dashboards.
In particular, NLG (or natural language generation) has been immensely important in the convergence of technical and non-technical users. Sophisticated NLG software has the ability to mine large quantities of numerical data, identify patterns and share that information in a way that is easy for humans to understand.
Forbes contributor Marc Zionts comments on the role of NLG in bridging the technical gap:
“NLG supports...any employee, regardless of role, position or level of data expertise to interpret the data being presented, what it means and what action to take in a way that translates visuals using the most natural form of communication - the written word.”
Such progress paints a clear picture of a future where data solutions will empower business users to make more data-driven decisions.
Salesforce’s recent acquisition of Tableau emphasizes that the most powerful BI solutions create dashboards and reporting that can be personalized for the business user’s needs. When data is available and easily understandable, more users are bound to find value.
The modern organization has amassed so much data that perhaps they don’t know what to do with it all. But rather than allow the sheer amount of data to overwhelm business users, they should invest in data analytics solutions that have practical applications for users across all functional departments: from marketing to IT.
A well-organized data strategy will drive improvements in the way your organization utilizes data. With this in mind, business users and data scientists can collaboratively implement the right software solution to support everyday business users to become citizen data scientists in the workplace.