Is data the new “oil”?

Is data the new “oil”?

OB- Is data the new "oil"?

By Oscar Barone, CEO of Conciliac

The phrase “Data is the new oil” has long resonated in the business world, but what is it all about and what is the real scenario in which companies find themselves today? 

Is data really a new source of global growth on all fronts like oil was? The impact that the exponential generation of data is having is empowering crucial decision making to get the most out of it, both for business and society.

We are entering an era where data will be crucial and its management – good or bad – will define many aspects of our lives.  It is an issue to be addressed and put on the agenda -not only technological- in order to generate best practices from the outset and thus obtain the best results.

The global big data industry is currently worth $274.3 billion.  Data interactions have increased by 5000% since 2010.  Without going any further, daily Google receives more than 3.5 billion searches and 100 billion messages are exchanged on WhatsApp.

The reality is that these trillions of data generated daily are accumulated, stored and at best some of them are visualized in dashboards.

To address this new era, technologically speaking, it is necessary to give way to exponential technologies (Machine Learning, Deep Learning, AI, Data Learning), which can process and manage the VolumeVariety and Velocity of current data creation. But which, in addition, and in case a “V” was missing, can validate the Veracity of the data to be used.

If we have dirty or false data, the information that makes up the reports is useless, and the decisions based on them are wrong.

Today, and even more so in the medium term, we will not be able to manage data and its new prominence with the technologies we used 20 years ago, as they are becoming obsolete. It is no longer just a question of where and how we store data and then export it to analysis tools. Databases as we know them will also have to adapt to these exponential technologies and reinvent themselves by including functional aspects of a new generation of needs.

Data exploitation must also be aligned in this process, through new paradigms, where reports are no longer analytical and become predictive in nature, minimizing the analyst’s intuition and providing more real probabilistic visibility.

To complete this very high-level picture, it is necessary to talk about the collaborative integration between different platforms, systems, and data-generating software as a key factor in the real-time availability of data and its validation.

With the goal of obtaining and working with the best quality through multiple validations, this is where automation and robotization of data management processes will be crucial for these channels to interact in a performant and transparent way.

But what is the mechanism by which we validate the integrity of that data to ensure its veracity or falsity?  Assuming that the data is truthful, will it be well used? And if the data is false and has already been used, is it better not to know?

We assume that organizations have a real data-driven strategy, but this is rarely the case.

To improve this aspect, roles are emerging that are becoming more and more relevant within organizations and will be fundamental for this change we are going through: Chief Transformation Officer, Chief Innovation Officer and Chief Data Officer.

Companies globally have begun to realize that improving data management is the next big breakthrough and are investing heavily in it. More than 62% of Fortune 1000 companies have hired Chief Data Officers (CDOs). 

They will be essential to follow the right path and its evolutionary stages, both in technological, strategic and cultural aspects. The objective is for data to be the factor that empowers accurate information and concrete predictive analysis, thus generating a planned, controlled and, above all, stable and real growth.

It is clear that, for a company, having large volumes of data available and organized is the first step. Validating and exploiting them to their advantage in order to compose strategic analyses is the fundamental goal in this new global business reality where the best use of data will be the best. Thus, the right technologies to manage them strategically are the ones that can lead an organization to be data-driven and have the agility and predictive capacity that this era demands. 


First publication: