In the era of Industry 4.0, big data is king.
But what are they?
Big Data: data characterized by large volumes, great variety and speed that require innovative processing processes capable of discovering specific insights, making decisions and automating processes. (Source: Gartner)
Big data are data that exceed the limits of traditional database tools, but this term also means technologies aimed at extracting knowledge and value from them. In practice, we could define big data as the analysis of incredibly large amounts of information and data, whatever their nature.
In consideration of their enormous extension in terms of volume, but also of their intrinsic characteristics of speed and variety, big data require technologies and specific analytical methods that can lead to the extraction of values of interest. The correct analysis of big data has the main objective of extracting additional information with respect to information that can be obtained from small data sets.
For several years now, the topic of big data has been considered particularly interesting by many companies, and investments in this regard are increasingly important.
Big data is important because the data will increase more and more with the advent of new technologies eg. 5G, IOT, etc.
Business intelligence is often not enough anymore.
Big data technologies use to inferential statistics and concepts of identification of non-linear systems to deduce regressions, causal effects and relationships from huge data sets. It also uses complex predictive models and heterogeneous datasets, that is unrelated to each other, to reveal the relationships and dependencies of these data, so as to be able to predict results and behaviors as accurately as possible while the business intelligence uses descriptive statistics with data with high information density, ie clean, limited datasets and relatively simple models.