"Present Future" - Summary

The exponential growth of data in modern society can be traced back to the period between 1453 and 1503, when Eisenstein reported that approximately eight million books were printed, surpassing the total written material produced in the previous 5,000 years of civilization. Fast forward to the early 2020s, and it is estimated that each individual produces almost two megabytes of data per second. By 2025, the creation of 463 exabytes of data is expected every single day.

This massive increase in data creation presents a significant challenge: how to turn vast amounts of data, stored in various formats, into useful information. Big data techniques address this challenge by analyzing correlations among thousands of variables without knowing beforehand which ones will be relevant. Algorithms then extract necessary recommendations from these correlations.

In just three minutes, more than 10 million Google searches are performed, around 1.5 million new tweets are posted on Twitter, and 1 million new stories are posted to Instagram. Every day, more than 2.5 quintillion bytes of data are produced, equivalent to 2.5 million terabytes. With such a massive volume of data, the challenge lies in extracting relevant information and using it intelligently.

Big data techniques work by using all available data, often processing it in a distributed manner and in parallel by several processors. This allows for the extraction of value from information generated by different business segments, potentially worth hundreds of billions of dollars. Virtually all sectors, both private and public, that produce data can benefit from the analyses performed by business intelligence systems. For example, analyzing data from social media about a sporting event can provide valuable insights for consumers and brands.