Big Data

Due to increasing digitization and data acquisition, more and more complex data volumes accumulate in many areas. They prove to be too changeable, complex, or weakly structured to be made usable with conventional data processing systems. The term Big Data captures these interrelationships. On the one hand, it describes the problematic data volumes themselves. At the same time, however, it also encompasses innovative IT solutions that allow mass data to be managed. So although there is no clear definition, the term Big Data as a whole stands for the phenomenon of mass data volumes and the associated processing practices.

Big Data can be defined by five key characteristics – the so-called 5Vs:

• Volume: large and complex amount of data; unmanageable or poorly manageable by traditional methods.
• Variety: large variety of data types and sources, which can be structured, semi-structured, or unstructured; relationships and structures can often only be created using a specific technology.
• Velocity: data processing must and should take place with increased speed
• Veracity/Validity: processing and post-processing of data is required concerning quality and credibility
• Value: by exploiting the data volumes, (corporate) added value can be achieved.