The big Data age is a belief in data science or the sense of leadership.

Even if companies have the ability to develop large data (and most do not), they tend to use untested ideas rather than using data science to make decisions. "Even in those companies that use data, many still have selective support for those that have been recognized rather than real data validation," says Guy Cuthbert, general manager of Atheon Analytics, a vision analyst, who uses the data itself, Just a disguise for making decisions by thinking.

In a recent roundtable at Actian in London, Cuthbert said that data science involves ways to make assumptions and test hypotheses, but most of the retail businesses he encounters bypass both methods.

"I can say a lot about the terrible stories of many retailers, and they all have one thing in common: they believe that customers have a particular way of behaving because they were told that on the day they opened," he said. They have never really questioned these statements to explore the real situation-the real situation of the category, the situation in a particular region of the country, or the size of the situation. Countless cases show that people are credulous of what others tell them, but they do not explore what the real facts are.

"We do a lot of work and want to change organizations from ' idea-driven ' to ' data-driven ' and let them start using facts and hypothetical scientific methods rather than ' taking it for granted '. "Cuthbert said.

Cuthbert said that he had tried to help many companies to understand the performance of their products, but none of these companies could be considered "analytical". According to his theory, about 1% or even 1 per thousand of the world's businesses are truly data-driven.

"I've seen a lot of companies that rely on intuition and don't know the original data to make decisions," Cuthbert said. I've heard too many executives gushing out all kinds of ideas that don't actually have any ' nutrition '. So if the data carvers or the data scientists do something to teach people about the fascinating data and the facts behind their organization, they will begin to recognize them consciously. ”

However, it is not easy to expose some (untrue) myths in the business and begin to accept the data based conclusions.

"When we present our views to people, we often encounter some of the gunpowder of the ' comeback ', they accuse us in person, said that we are talking about ridiculous." "Cuthbert said.

Another problem is that even if companies try to use data scientifically, their focus is too focused and parochial.

"Most of the companies we work with are focused on what's known, and they're always looking at things like ' we want to increase our revenue by 6% next year and let's make sure we get 6% '." "Cuthbert said.

"They didn't look for an increase of 30% or 120%. A lot of our work is just floating on the surface, or showing things that they don't really understand themselves. ”

Unfortunately, although technological advances allow us to deal with billions of of data very easily, the analysis itself must be done with human resources.

"The lack of inspiration in machines is the current cause of the huge gap between machine learning and other computer technology and human thinking," he said. "Cuthbert says," inspiration comes from people who know how to find hidden information from the data. ”

"Until now, to meet the development skills needed for large data, they have a specific set of high budget customers who need these skills to complete the project," said Steve Shine, CEO of Actian, a big data analyst.

"In the last three or four years, if you've ever touched a Hadoop project in any one place, you realize that it's a pretty good skill to write an efficient MapReduce program and make Hadoop run efficiently." "This skill has been enthusiastically protected by the tech community but has not spread, but dramatic changes have taken place in the last 12 months," Shine said. Everyone accepts the need to make it easier to take advantage of new technologies. ”

"We bring people back to the 80 's, and if you have the ability to get all the data and discover new insights through code now, how productive you will become." ”

But now the new problem is that large data technologies are proliferating, with various versions of Hadoop, NoSQL, and new ways of providing and consolidating data.

"No CIO has been rewarded for putting these things together," he said. Companies don't care how quickly and how well you glue them together. Companies don't care how quickly you can help him find customer churn data. "Shine said.

However, today's technology allows companies to discover unexpected business potential from their usual production data.

Shine quotes his client in the welfare and payroll services sector, where information about wage changes, graduates, and participants is more accurate than the information the Government provides to portray macroeconomics.

He said: "Those organizations that look traditional, there is actually a business in which they realize that if they are data-centric and use data and, as much as possible, combine other data they can get, they can basically make something that is fundamentally more valuable than what they can do now," he said.