Big data use cases and the big data wake up call

According to recent studies on big data readiness, the majority of companies (more than 60 percent in the latest study of Crisp Research) are not prepared for the challenges of digital transformation. In fact, 58 percent of decision makers surveyed say they have no strategy in place.

The quest for the golden use case

Aside from industries and companies that are forced to invest in big data due to their business model (telecommunication and retail, for example), the first steps for the majority of companies in the DACH region are still very hesitant. Most companies are in a process that I like to call "searching for the golden use case," meaning they think they understand the importance of big data so they start searching for the groundbreaking business case. This case has to prove in a short timeframe that big data is worth the investment. Very often, the result is: nothing.

Faced with unimpressive results, early adopters are asking, are the claims about the huge benefits of big data just more hype, or are we doing something wrong? Where are the big data use cases? And how can we do the same?

If we talk to leaders in enterprises, we get a clear answer: According to a recent study by Accenture and General Electric, 87 percent of enterprises believe big data analytics will redefine the competitive landscape of their industries within the next three years. 89 percent believe that companies that do not adopt a big data analytics strategy in the next year risk losing market share and momentum. Obviously, no hype.

Why risk missing the big data train?

Indeed, there are an increasing number of successful big data use cases from the DACH region as well as from international regions. Let's pick three representative examples:

1.A large retail bank reduced the operational costs of its data warehouse by migrating significant parts of the warehouse from a mainframe environment to a Hadoop platform. The company was not only able to reduce the load on the mainframe and realize significant cost savings, but to accelerate the processing time of all its data exponentially.

2.A large telecommunications provider in Italy decided to gather network coverage data from its competitors by very creative means. The company's vision was to improve its marketing activities and to derive information for investments in its own infrastructure. Only big data technologies could have provided storage for these large amounts of data over a longer period. In-memory analytics technologies were used to recognize potential correlations and to operationalize these models in real-time business processes.

3.One of the world's largest oil companies uses innovative sensor technologies in combination with big data analytics to identify early warnings in the drilling process. A predictive maintenance alert at the optimum time helps to avoid huge costs through unnecessary failures or unnecessary exchange of very expensive material. At the same time, the maintenance team resources can be optimally scheduled through all of the company’s drilling rigs assets.

These real-life examples prove that the use of big data technologies can provide significant added value to the business and lead to a competitive advantage. Big data is not a trend that will disappear after a first hype back into oblivion, but something that has high potential for savings through modernization or the implementation of new business processes. Digital transformation applies to any company and will change processes dramatically. Sooner or later. But it will.