By Stéphane Amarsy,
Chairman of the board of Splio + D-AIM
The term “Big Data” is a common buzzword in today’s business world. But as with many trendy concepts or ideas, it is often misappropriated. However, the core concept of Big Data marked the beginning of a new era with three important tools: Smart Data, data lakes and programmatic marketing and algorithms/AI.
Data is now a vital part of the decision-making process within most companies. It uses figures and analysis to create efficient strategies and ensure a relevant approach to both internal issues and the customer relationship. What’s more, Big Data is a great opportunity for companies looking to innovate, expand sales, profits and markets, acquire new customers and create new offers. It is also an endless source of information for algorithms that learn, reproduce, predict and help us make decisions. And with richer data, algorithms will become even more powerful.
Even greater amounts of data
Companies only use a small part of the data available to them. The collection, storage and exploitation of data has been extremely costly thus far. Processing large amounts of data is more expensive than the value its use would generate. Volume is another factor that determines our approach; making sense of so much information is human impossible. Instead of tackling the impossible, we must leave it to mathematics before providing a specific context for use.
The data become actionable, but the pursuit of exhaustiveness remains a major challenge. Conclusions taken from data are more accurate with greater volumes of data to start from.
So much now lies within the realm of possibility, but there are numerous legal, ethical and operational limitations, especially when collecting and storing all the data.
Too much or too little data?
Data is the gold rush of the digital age, but the asset is intangible. The lessons of the past are rarely used. Once again, we are witnessing a profusion of projects launched solely from a technical point of view. But with little consideration for the objectives, many of these projects are—or will be—a failure. This type of approach has only disadvantages:
increased costs, little in the way of change management, an “elite” of experts who often struggle to share and explain their work and complicated marketing that fails to gain consumers’ trust.
Projects based on such an approach can only succeed if led by a multi-disciplinary and versatile team. Working together towards well-defined goals will also promote ownership and therefore drive change. Data collection must first focus on what’s most relevant for the problem being addressed before broadening its scope. This is where Smart Data comes in.
While Big Data and Smart Data are among the biggest trends today, they are just in their infancy. But their application is not some fad. Instead, these approaches help companies create value by working with data in a more profound way, with technological capabilities that have only recently become available. These technologies will, of course, continue to evolve, bringing with them new uses and experimentation. Many of them are just getting started and, in the future, we will surely see others that now seem unimaginable.