Big Data: Myths vs reality

The phenomenon of big data (understood as the ability to generate, record, process, analyze and obtain intelligent information from a huge amount of data) is marking a before and after in many aspects of life and could be equivalent to the revolution that led to the development of the Internet. No business area or segment of our life is going to be left out of the reach of big data and its exploitation, for example, by artificial intelligence. There are not a few authorized voices that defend that the result of this pandemic would have been different if they had had better data to analyze.

Let’s get an idea of ​​the dimension of what we are talking about. Already in 2012 – practically 10 years ago – the giant IBM stated that if all the bytes of data that we generate annually were saved on CDs and we piled them up, we would create a great round-trip tower from the Earth to the Moon. Since then, the increase in data has been exponential.

And it is that cities are full of sensors that collect weather information, traffic, financial transactions, our footprint on the Internet, in social networks, in purchases, in the consumption of content, in how we travel, our health … We are the users and citizens anonymous, those who leave an impressive data trail, not only of what we do, but also of what we think and even how we feel.

Data as a bargaining chip

Data is the new bargaining chip. They are the new power. A few years ago, terrorist groups from the East discovered the location of American military bases in the area from access to data generated by the wearables of American soldiers… and yet we shared our data without thinking twice.

We hate constantly entering our password so we “log in” to “unknown” pages using our RRSS with applications such as Facebook or Google. As consumers and individuals, our lives – our preferences, passions and prejudices – are encapsulated in many terabytes of data, in the cloud: from our purchase history on Amazon, through what we like on Facebook and Instagram, to our opinions on Twitter, who are our friends or family, what we Google and what we ask Alexa or Siri.

To capitalize on this opportunity from brands and companies, it is necessary to understand what big data is and what it is not and how we can apply it to our work. Next, we explore seven myths against as many realities around big data:

Myth 1: EVERYONE USES IT

The companies that are actually using their big data are very few. There are many top managers who are very interested in what it can offer, but when it comes down to it, they find it difficult to take the step towards a true digital transformation because of the ‘fear’ inherent to change. A strategic use of big data is not so widespread and, of course, much less in the field of communication and marketing.

According to the report “Digital maturity in Spain. Data and Analytics ”of Indra’s subsidiary, Minsait, only 17% of the companies in our country had specialists in data analytics at the end of 2019.

Myth 2: MORE DATA = BETTER DATA

When people talk about big data, the conversation is usually about the amount of data and how this amount grows. Size and speed seem the most important. Size is not really that relevant because, in fact, a very small percentage of all available data is actually being used today.

The most important thing is the quality of the data. What makes big data really useful are the so-called 5 V’s:

  • Volume – How much data do we have?
  • Variety – In what formats and with what variety of sources do we have the information?
  • Speed ​​- The speed at which new data is generated and added to existing data. Also the speed at which we can analyze them, if it is in real time, for example.
  • Veracity – The quality and veracity of the data we have. The degree of trust.
  • Value – The value they bring us through their analysis.

Myth 3: YOU NEED A LOT OF MONEY

It is true that large corporations and governments are investing large budgets in hardware, software, storage and professionals with skills in these fields but, with each passing day, big data technology is getting cheaper and also increasing the number of software options that allows the analysis of that data. Increasingly, the use of big data is democratizing, allowing all players – from the largest to SMEs – to start developing their data-driven strategies.

Myth 4: LEADERS SUCCEED WITH TOOLS AND TECHNOLOGY

It is obvious that tools and technology are important, but it is not what the success of big data is based on. Success with big data is based, above all, on a company structure and culture based on data analysis. Being “data-driven” is more important than having a lot of data. Studies show that the more “data-driven” companies are considered, the better their performance and results. Being successful with data also requires fostering a culture of experimentation.

Myth 5: THIS IS ABOUT IT PEOPLE, MATHEMATICS, ENGINEERS, ANALYSTS …

Everyone wants to “build big data”, but very few people know how to structure this cycle. And, above all, the big question is what for? What do we want to know?

Big data in itself is worthless. The question is not how much data we can have or analyze, but what we want to analyze it for, what we want to know, and therefore what kind of data we will need. And to adequately answer this, although it may surprise us, it is often necessary to have minds with a more “humanist” profile than a “science” one: philosophers, sociologists, linguists …

The skills needed to use big data are only 50% technical or statistical. The other 50% are logical thinking: knowing how to formulate good hypotheses based on what we know and what we want to discover. The challenge does not lie with the data, but with analytical thinking: the ability to recognize and solve problems using available information.

Myth 6: BIG DATA IS THE NEW OIL

Yes effectively. Despite the fact that the use of data to obtain information is nothing new at all. Like oil, data is useless in crude oil, it has to be refined and transformed into gasoline. Also big data is like a kilogram of flour or rice. They may have some value, but if we don’t know how to use them to make a recipe, they have no value because they are not edible.

Myth 7: ALL DATA CAN BE ANALYZED

There is a vast amount of data that cannot be tracked, measured, or analyzed. It is the so-called “dark social”: for example, all those visits to a website whose origin is unknown. Or all the occasions in which we share information via email or instant messaging such as WhatsApp, Snapchat or Messenger. This data traffic is difficult to measure and essentially nearly invisible to most analytics programs. Several studies assure that the “dark social” supposes, at least, 50% of the traffic of any web.

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