How does Big Data and Analytics work? Simply Explained

Big Data

Data, there’s so much of it that even the term Big Data doesn’t seem to describe it accurately. It feels more like Huge Data, or Gigantic Data, right?

To make Big Data less abstract, it can help to break it into four dimensions of which the sheer amount of data is just one aspect. The others are types of data: videos, photos, texts, structured data in spreadsheets, you name it. Then there is the speed at which all this data can be processed. And finally, there is the reliability of data.

Together, these dimensions also determine the value of data. Companies and individuals can be flooded by data. One drop of data is pretty useless. But when you collect a bucket or even an ocean of data You can start to see patterns that may lead to useful insights. But as we’ve said before, the value of data is not in having a lot of it.

You need to use the right data. Using that data intelligently can make a huge difference in the world. In the most popular sport on the planet, for instance. Football. More and more clubs use big data to gather statistics on the players: their top speed the distance they run in a match, the accuracy of their shots. The next step is analyzing this data.

That is where analytics tools come in: they can help you make sense of the huge amounts of data and allow data to be transformed into insights. Information that can help coaches to come up with personalized training programs and optimal game strategies or scouts with selecting the most promising talents. With predictive analysis it’s even possible to predict what is going to happen. Finally, the data can be made available to others, like the fans.

Making data available beyond your own organization is known as Data Intelligence. For companies, rather than football clubs, Data Intelligence offers the possibility to aggregate and anonymize data to be made available to a wider community. The challenge is no longer how to harvest it, but how to use it in smart ways.

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