big data
Big Data stands for unimaginably large amounts of data, measured in zettabytes(ZB) or even yottabytes(YB) and used as a resource. Big Data, which is synonymous with a Data Lake, is about collecting, evaluating and analyzing data in order to use it for marketing services and products or for monitoring purposes.
Big data analytics is used to analyze usage patterns of prospective customers from the huge data pool, to create movement profiles or to calculate precise predictions and forecasts about information, purchasing and usage behavior. It involves the analysis of mass data in which data from a wide variety of data types are set in relation to each other or correlated with each other.
The different characteristic features in the processing of extremely large amounts of data are adequately described by the terms Volume, Variety and Velocity, which are referred to as 3Vs. The volume of Big Data referred to was created by low-cost storage that allows any type of information to be stored: Booking and payment transactions, location data of mobile phone users, search engine inputs, weather data, motor vehicle routes and speeds, traffic flow data, road accident data and patient data, data from research facilities such as Cern's Large Hadron Collider (LHC), human genomes, etc. Social networks such as Facebook, Xing or LinkedIn also offer incredible potential for personal data, as do various apps designed as data collection applications.
Big Data is a trend that can be seen in the marketing of personalized data, but it can also be used to make predictions about future events. These can be predictions for elections, predicted energy needs, survival rates for certain therapies, locations and times where a crime is most likely to occur, or used to sell a particular product. In the latter application, there is enormous potential for savings through optimized supply and appropriate inventory management.
If the Big Data data is processed and analyzed almost in real time without any latency worth mentioning, this is referred to as Fast Data.