To refute myths regarding Big Data, one has to first understand the basic concept of what it is. Turns out that it is not that simple. One indicator to the fact it is slightly hard to understand, is the multitude of publications trying to point to common misconceptions about Big Data.

Not only are there a lot of such misconceptions in a relatively short amount of time, but there is apparently some disagreement among critics about what exactly are these misconceptions.

First, hat exactly is Big Data? Well, every day the amount of information, content, digital traces and any kind of online data – stored or not, encrypted or not, machine or human read – increases. These volumes can be described as “Gazillions in the power of a lot”, in a hard to track pace and in a variety of forms from a variety of sources. These form the concept of Big Data. Organizations which gather an enormous amounts of data on a daily basis, such as Google and Facebook, are using tools such as Hadoop to analyze the data and gather new insights from it: hidden interconnections, market preferences and also, according to statistics and probability – future predictions, regarding possibility of crime perpetrated by specific persons in a specific place, or the chances of an academic candidate to drop out before graduating.

Various domains – advertising, business, computer sciences – take different approaches to the matter: Every approach has its own list of misunderstandings. Here are some articles pointing out to the biggest myths regarding Big Data. Digiday,for example, lists the The Urban Legends of Big Data: They include, among others, “Big Data is for big business” and “the more data the better”. InformationWeek  has a different list: “If you don’t move to Big Data you will lag behind”, “Big Data is an IT problem” and “Big Data requires costly data scientists”. These are just two out of dozens and it looks like every new article is more confusing than the previous.

 From the point of view of the common person, I narrowed it down to these 3 common myths:

1. Big Data will make all of our decisions for us

Will Big Data be blocking academic candidates from enrolling into disciplines they will likely fail to graduate? What about preventive incarceration for potential offender? Along with the expectation that Big Data based decisions will be better, will benefit effeciency in governments and organizations, there is a fear that automating such decisions will eliminate the human factor. The good news is that we are already living in a bureaucratic world where people are the ones making decisions such as revoking your social benefits, deny your job applications and other such niceties. Big Data will not change this. People will still be the ones making the decisions. They will simply be better aware of the big picture and make more intelligent decisions.

2. Big Data will take away my job

Let’s face it, some professions are going to disappear, since in a changing world, employment also changes. Shoemakers and record shop sellers are already a rare vision these days. With algo-trading and robotic systems, brokers and telemarketers are going to follow. This has nothing to do with Big Data. There is an existing worry about Big Data and robots challenging existing professions like doctors and pilots – but changing reality brings new needs,which bring new professions to meet those needs.

3. Big Data is for infographics and targeted advertising

Unlike the above two myths, which may be exaggerating the potential threat of Big Data to the current state of things, this myth is seriously underestimating it. Information can be formalized in various ways. Infographics is one of them and if done well, it can be a great method to visualize quantitative insights. Other than that, if Facebook’s ad targeting system finds a regularity of adjacent events and use this information to sell you stuff when you are most likely to be impressionable, that will indeed be a case for targeted advertising based on Big Data. But that is just a narrow usage of Big Data. There are so many possibilities for Big Data and we haven’t even began to scratch the surface.

Posted by Samuel Miller

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