When we talk about Big Data, we refer to data sets or combinations of data sets whose size, complexity (variability) and speed of growth (velocity) make their capture, management, processing or analysis difficult by conventional technologies and tools such as relational databases and conventional statistics or display packages, within the time required to be useful.
Although the size used to determine if a given data set is considered Big Data is not firmly defined and continues to change over time, most analysts and professionals currently refer to datasets ranging from 30-50 terabytes to several Petabytes.
The complex nature of Big Data is mainly due to the unstructured nature of much of the data generated by modern technologies such as web logs, radio frequency identification (RFID), embedded sensors in devices, machinery, vehicles , Internet searches, social networks like Facebook, laptops, smartphones and other mobile phones, GPS devices and call center records.
In most cases, in order to effectively use Big Data, it must be combined with structured data (usually from a relational database) of a more conventional business application, such as ERP (Enterprise Resource Planning) or CRM ( Customer Relationship Management).
