Data systems are the technology that collect, store and allow access to data that drives organizational processes. They may include the database management system (DBMS) and data warehouses, data platforms that are specialized such as NoSQL databases and alternative storage methods for data such as file systems or cloud object storage services. They also can include master-data management, which creates an organization’s common set of information for its products, clients, or other assets.
Volume as well as variety and speed are the main characteristics of a successful data management system. Volume refers to the volume of data being processed. It can be large data sets that are too complex for one computer to manage. Variety refers to different types of data that are being collected from traditional sensors, feeds from social media, and other sources. Velocity refers to the speed of data that flows through and out of read the data system.
These four attributes have triggered the creation of new and innovative data systems. In addition to the conventional databases and DBMS technologies there are now a variety of new data platforms that can handle a large variety of data.
A large sensor data systems like this one, for instance, is a networked set of sensors and devices that gather a large variety of data from physical sensors such as smartphones or wearable medical sensors. The readings from sensors can include location, signal or image information along with timestamps. The data is stored on the device and then transferred to a server. The data is then preprocessed to ensure that it is safe and meaningful enough for processing and analysing.