Data systems are the framework that collects, stores and makes available data that businesses use. Data systems include the database system (DBMS) warehouses special platforms, such as NoSQL databases and alternative data storage models like cloud object services. They could also include master data management, which is the process of creating an unified set of reference data for an organization, its customers, products, or other assets.
Volume speed, variety, and velocity are the main characteristics of a successful data management system. Volume refers the amount of data that is processed, often in very large and complex data sets that cannot be handled by one computer. Variety refers the various types of data being gathered, from traditional sensors as well as social media feeds and other sources. Velocity refers to the speed at which data flows into and out of the data system.
These four traits have led to the development of new and innovative data systems. There are new data platforms which can handle a diverse range of data. These platforms are in addition to the traditional databases.
A large sensor data system for instance, is a networked system comprising devices and sensors that collect a vast variety of information from physical sensors such as smartphones or wearable medical sensors. These sensor data readings can include location, signal or image information as well as timestamps. The data is then stored on the device and sent to a central server. The data is then preprocessed to ensure that it is clean and meaningful enough to be suitable for processing and analysing.