The analogy between data and oil has fascinated both technology industry thinkers and marketing types. But are the similarities between the role of data today and that of oil yesterday enough to substantiate the comparison? Or is the analogy inaccurate in framing a phenomenon that is not yet very well understood? Wael Elrifai, Senior Director of Enterprise Solutions with Hitachi Vantara, makes the case for the latter.
Some of the key properties of oil are that it’s a fossil fuel and a finite resource. Its price is subject to market valuations depending on supply and demand. It’s a raw material that can be converted into energy and can also be turned into many other products, from garbage bags to
On the other hand, unlike oil, data isn’t one specific thing or form factor. Data is just a code used to describe something. Data can come in many forms, such as text, numbers or dates. It can also be part of a video stream, structured in tables or freeform in documents.
Data, in addition, is an infinite resource. This sounds significant, but it also raises a unique set of problems compared to those of finite resources. For one thing, to derive value and make predictions from data, useful signals that trigger events and decisions need to be separated from massive amounts of irrelevant background noise. This is very important in the world of IoT because sensors generate high volumes of this noise. These signals, however, are essential for predictive maintenance and other use cases.
“Dark data” and the laws of supply and demand
Another challenge brought about by data’s endless nature involves figuring out how to manage and use available useful data, including so-called dark data. Gartner defines “dark data” as the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes – for example, analytics, business relationships and direct monetizing. Information assets are often hidden in dark data, which is why many companies hang on to it for compliance reasons. It’s expensive and risky to store and secure this data, so organizations are now exploring ways to derive more value out of their dark data.
Countless articles in respectable publications have hailed data as “the new oil.” Now I appreciate a colorful metaphor as much as the next engineer, but I’m concerned that this comparison could lead some people down the wrong path.
Data’s boundlessness also means that it’s not subject to laws of supply and demand. The extent to which data turns into commercially valuable insight depends on how signals are extracted from noise and on how algorithms are made contextually smarter over time – either through human intervention or machine learning.
A resource that keeps on giving
So far, data can’t be converted into energy, at least not in any practical way. Data can however, be refined, or in other words, cleaned and structured, and analyzed, or converted into information. Once analyzed and presented to people, it can be used for decision making. The quality of data-driven decisions can have a huge material impact on business.
Data can be considered a raw material, but with some important differences. For example, unlike oil, the same piece of data can be reused in different applications over and over again without eroding in value. Take my Facebook login details, for instance, which can be used to access a number of different apps on my phone.
Interestingly, in Latin, data is the past participle of the verb “to give.” Indeed, data will be a resource that keeps on giving. There are already many cases in transportation, industrial manufacturing, shipping and cities where data saves money, prevents injuries and improves services. But please, comparisons to oil must stop.
Text: Wael Elrifai