What is Big Data Analytics
90% of the data available in the world today has been created over the last two years. We find ourselves in the age of big data. But what does this mean exactly? Big data analytics is the study of huge amounts of stored data in order to extract behavior patterns. These data are characterized by the high speed they are being generated with, the huge volume they represent, the immense variety of typology they encompass, and the degree of veracity they are.
More than 2.5 trillion bytes of information are generated every day through our smartphones, tablets, GPS devices, sensors spread all over our cities, bank cards.
What can be done with all this information?
This is where big data analytics comes into play with a combination of high technology systems and mathematics which together are capable of analyzing all this information and providing it with a meaning of great value for companies or governments.
- Find pattern
Types of Big Data Analytics
There are four types of big data analytics:
- The descriptive one – explain to what happened in the past based on data presented through graphics or reports, but not why or what will happen in the future.
- The diagnostic one – closely linked to the previous type seeks to understand the reasons why any given event took place in the past.
- The predictive one – the most useful for companies goes through data in order to predict what could happen.
- The prescriptive one – an evolution of the preceding approach based on automation processing or a/b testing. The system decides analyzing and predicting data advices on how to proceed according to them by recommending for example the best location on your site to place a banner or the most convenient gas station along your way if you want to avoid traffic.
Big data analytics helps companies or public administrations to understand the users better find previously unnoticeable opportunity, provide a better service and these on mitigate fraud. The revolution of datafication is just beginning.