Because of the rapid expansion of structured and unstructured data produced by companies and individuals, there will be more data than grains of sand in the world in just five years. It's a staggering statistic, and Kenneth Cukier says businesses need to recognize the crucial relationship between big data and cloud computing.

It's not that complicated

“When all the data is stored in the same place, running big data applications is easier — and cloud computing simplifies that,” explains Cukier, co-author of “Big Data.” “It was outrageously hard to manage, and it was virtually impossible for the data to be combined and used as a corporate asset and strategic lever.

“Once the data sits in the cloud, it’s easier to integrate it into new business processes or combine with other data for analytical insight. Cloud computing is a huge enabler of big data activities in business and scientific research. And big data is giving organizations a new justification to go through the process of shifting IT operations to the cloud.”

The numbers tell the story

Experts at the Computer Science Corporation estimate that by 2020, there will be a 4,300 percent increase in the amount of data generated annually. Information is now being stored so quickly and from so many sources that traditional IT management and analytic software doesn't have the capabilities to properly manage, store, process and analyze it.

A longtime business-technology journalist, Cukier realizes how data is changing the business landscape and international competitiveness:

“As a keynote speaker at corporate events, I’ve seen how senior managers need to change corporate cultures to get the most from cloud computing and big data.”

“The most important question is: Does big data have top management buy-in? Without that support, big data is a dead duck.”

Asking the right questions

Cukier says that before investing in big data solutions, companies shouldn't initially focus on what they'll do with the technology.

“The most important question is: Does big data have top management buy-in? Without that support, big data is a dead duck. Next, the questions are: What data do we have — and is it in the right form to be used? What other data do we need and how can we get it? Do we have the right people or do we need to fill gaps, so we know what kit to buy? Finally, do we have the right culture to listen to data and change our processes, or do we need to work on that as well?”

Thinking outside the box

Cukier says the German e-retailer Otto is a prime example of getting creative when using big data to save millions.

“It found that shoppers were more likely to return items if they arrived after more than three days. So, to improve service for customers and protect its margins, it needed to ship goods faster. To do that, it built a predictive model using an advanced algorithm by Blue Yonder that was originally developed for analyzing experiments at CERN, a particle physics lab. The algorithm analyzed around 200 variables to predict what shoppers would buy a month before the purchases actually happened. Then, Otto would buy the goods, so it could ship them right after the order.”

What's ahead?

Cukier also says business analytics have had a tremendous impact on marketing, which is next in line for a revolution.

“The good news is that marketing performance can be measured and, finally, the industry is putting more science around their practices and less art. The drawback is that the practice of marketing is indeed black magic: a special bit of creativity and excellence will be lost if all decisions need to pass through a big-data RIO filter. The key will be marrying the data to human ingenuity.”