Big Data refers to a large amount of structured and unstructured data that accumulates in a company. This is data that is, for example, too large, too complex, too fast-moving or too weakly structured to be evaluated using manual and standard data processing methods.
The “Big” in Big Data refers to four dimensions (the 4 V’s ):
Scope and the volume of data. This includes data such as business transactions, IoT, industrial plant, videos, social media, among others.
Speed at which data volumes are generated and transferred. Data volumes from RFID tags, sensors and smart metering fall into this category and are handled in near real-time.
Range of data types and data source. Structured, semi-structured and unstructured data describe the variety. Approximately 90% of the stored data is unstructured and is often not even evaluated by databases. Big Data makes it possible to analyze these using machine learning.
Authenticity of the data. In some cases, data from various sources does not arrive in the desired quality and can therefore not be used as intended or must be reprocessed at great expense.