Birst's Peters emphasizes the importance of user training and corporate governance to ensure that tools are used appropriately.
It's also possible that the risks of misuse are no worse than those associated with any business-intelligence tool, Tableau's Ajenstat said: "It's always possible for someone to make a decision based on bad data or a bad assumption."
Still, it's unlikely that "out-of-the-box" analytics will succeed in situations where the end-user is not properly trained and lacks experience in best practices, Borne said. "I think that a person without a formal analytics education but with good data literacy, numeracy, curiosity and problem-solving skills will probably be okay, but only after tutorials and training."
The spread of analytics may become even greater over time. Analytics APIs and out-of-the-box toolkits, in particular, will "sell like hotcakes" to Internet-of-Things entrepreneurs, startups and innovators as well as to the big incumbents who "see the value in enterprise solutions when compared against expensive, in-house, custom-built, R&D-intensive solutions," said Borne.
In fact, enterprises will eventually begin automating more and more high-level analytics capabilities, he predicted, with fewer and fewer humans involved.
Gregory Piatetsky-Shapiro, president and editor of analytics-focused KDnuggets.com, had a similar view. Automated and embedded analytics will increasingly take hold, followed eventually by a greater use of artificial intelligence and machine learning, he said. As part of that diminishing human involvement, a number of professions could be particularly at risk, including lawyers, accountants, marketers and financial advisors.
Reporters were also on Piatetsky-Shapiro's list, though he did offer a note of temporary reassurance. "Computers can use data to generate articles," he said. "Like this one? Not yet."
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