Data analytics projects are deflating at a rate of 85 percent, according to some analysts. The culprit is not likely a lack of software tools — the market is brimming with them. Rather, it’s cultural hiccups to blame. One such obstacle is the low degree of transparency and trust in data analytics across entire organizations.

“Right now we have kind of the high priesthood of analytics going on,” said Stephanie McReynolds (pictured), vice president of marketing at Alation Inc. “And some believers will believe, but a lot of folks won’t.”

Even if a company can snag one of the scarce data scientists or chief data officers available, that individual will likely not suffice, according to McReynolds. For one, he or she will have to endlessly proselytize to skeptics in different departments; also, a single data scientist’s brain is not scalable for large companies. Companies must demystify data analytics and make the practice doable for regular business people, she added.

McReynolds spoke with Rebecca Knight (@knightrm) and James Kobielus (@jameskobielus), co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the DataWorks Summit in San Jose, California. They discussed do-it-yourself analytics and the better-together relationship between artificial intelligence and people. (* Disclosure below.)

Training, cataloging detangle analytics hairball

People are more trusting of data analytics when they know a human looped in for final decisions; they also feel more comfortable using algorithms themselves when they understand the nuts and bolts of how they work, McReynolds explained. The more dense and geeky the terminology around data technologies, the more it will scare off business people.

“Most people in the business are just getting their arms around ‘how do we trust the output of analytics? How do we understand enough statistics to know what to apply to solve a business problem of not?'” she said. “And then we give them this hairball of technical artifacts and say, ‘Oh, go at it.'”

With the General Data Protection Regulation now enforceable for any business with European operations, the need to simplify data analysis is more pressing than ever — and many companies are failing, McReynolds pointed out. Some of Alation’s customers have kicked off data-literacy programs, which McReynolds’ applauds. Alation’s data cataloging technology synergies human and AI for plain-English data labeling and analysis.

“One of the things that we can do is continue to help by building out applications that make it easy for information stewardship,” McReynolds concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the DataWorks Summit. (* Disclosure: Alation Inc. sponsored this segment of theCUBE. Neither Alation nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE