Big data: from the Romans to Steve Jobs, Google and today

Hester Gras

Publishers are pelted with publications screaming data, data, data and the only thing they think about is: get me some data too. But do they actually know what has changed, except for the fact that it opens up new opportunities for making money with content? I think, for many of them, the answer is no. So let’s take this story back to its beginnings to find out how our understanding of information technology has opened up opportunities we never even dreamed of before. (for a detailed story, I advice you to read ‘De Big Data Revolutie’ by Kenneth Cukier and Viktor Mayer-Schönberger).

big data on digital magazines are a solution for analyzing digital reading behavior on tablets and smartphones

1, 2, 3 … 100.000?
Every story has its beginning, so does big data. I won’t bore you with a history lesson, but I do want to tell you an interesting fact about the Romans, NY. In 1872, the U.S. Census Office decided to organize a census. But how were they supposed to do this with over 100.000 people and no automatic systems? It took them eight years to finish it! And even worse, the next census was forecasted to take thirteen years. Luckily, an American inventor named Herman Hollertigh passed by and introduced an automatic process that reduced the census time from eight years to one. In the years that followed, people began to adopt samples.

Today, we can do smarter things
Nowadays, we have more data than ever before. However, we also have newer, faster and better technologies, which give us the possibility to do smarter things. Steve Jobs, for example, invested in big data and asked scientists to explore his complete DNA profile to make customized medicines for himself. “If it doesn’t help me, it will help others in the future,” is what he said. Unfortunately, it didn’t save him. But his story illustrates that data gives us the possibility to do smarter things and even save lives.

Or take Google, for instance, which was able to forecast the flu epidemic in Spain solely based on search terms and the locations of Google search engine users. They didn’t need data from doctors, nor did they need the exact flu symptoms. The only thing they needed was the right search terms.

So, what exactly has changed?

  1. N = Everything
    Why should we still use sample sizes if we have the possibility to process all data? Today, we can collect every single data stream and find details that often would have been ignored when analyzing one sample. Big data allows us to get a complete and detailed picture.

        2.  More data is preferable above better data
Earlier on, we tried to remove all inaccuracies. This was partially possible because small data allowed us to do so. A sample could not contain mistakes because it was too small and too sensible. When it comes to big data, we are willing to include inaccuracies because the amount of data is so high that it isn’t too risky to make mistakes anymore.

         3. Goodbye causal relationships
Because today’s data is big, it’s easier to gain insights into patterns, forecast new ones and predict consumer preferences (of course, we can never be certain about our predictions, but a probability is valuable too). Therefore, it isn’t important anymore to know why, because it is enough to know that there is something (like Google and the flu epidemic).

But… big data alone won’t help you
Big data is very useful, but just as Google, you have to know where and what to look for. When you look at the right elements, big data can help to optimize your product. Today, data won’t be out-of-date anymore because it doesn’t take eight years to analyse. Data is available in real time, which makes it easier to see patterns of users, forecast new ones and step into a new market. Finally, you can target a specific audience, make individual recommendations, and closely examine reading behavior: what are users reading, how engaged are they? These days, you can improve your product simply by asking the right questions.

But things can also get complicated. Analyzing data is expensive, takes a lot of time, needs the right focus and above all, data needs to be available. At imgZine, we help you analyze big data to understand your audience’s reading behavior on tablets and smartphones. With our insights, we want to make our digital publishing software even more successful for customers. Above all, we believe that sharing knowledge will improve the publishing ecosystem all together, so we’d love to share our insights with you.

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