"You wouldn't have just one department creating spreadsheets that no one can modify," Biewald added. "Modern businesses need to think about these data tools in the same way they think about Excel."
Gartner predicts that the market for self-service data-preparation tools will reach $1 billion by 2019.
"Large enterprises are moving to data lakes, so all the data is in one place," said Jason Zintak, Platfora's president and CEO.
Next, companies need to help their employees make the most of it. Platfora bills its Hadoop-focused platform as a way to let anyone within a company run analyses across the entire organization's data, including transactions, customer interactions and machine data.
'They can build their own reports'
In many ways, the citizen data scientist represents an evolution of the traditional business analyst role.
"When I think about the traditional business analyst, they'd have a good understanding of the business but were not necessarily conversant with regard to the data," Sears' Pickett said.
Such professionals have often been focused on gleaning insights from Excel or other reporting tools without necessarily working knee-deep in the data, in other words.
In today's data-rich era, there's better literacy in terms of what data-focused questions to ask, Pickett added, reflecting the move from relational databases and spreadsheets to data lakes and more sophisticated analytical tools.
"What I'm observing is that people who have a strong understanding of the business now have some capability in terms of the data," he explained. "They can build their own reports, they know what attributes go together and they know what questions to ask not just from a business perspective but from a data perspective."
Not everyone is sold on the citizen data scientist concept, however.
'A recipe for disaster'
"I don't like the 'citizen data scientist' term," said Gregory Piatetsky-Shapiro, president of KDnuggets, an analytics and data-science consultancy.
For one thing, "the term implies that people without much training can do the work of a data scientist," Piatetsky-Shapiro said.
It's all too easy to discount the importance of education, in other words, even as big data is in many ways making it more important than ever before. With statistics at its core, data science often relies on an understanding of the assumptions underlying various statistical techniques, for example -- factors that aren't always apparent to those who haven't formally learned about them.
"Would you trust your teeth to a 'citizen dentist' or fly in a plane piloted by 'citizen pilot'?" Piatetsky-Shapiro asked. "Having untrained citizen data scientists analyze the data may be easy, but if they will be making decisions without proper training in data analysis and without an understanding of the business, it is a recipe for disaster."
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