Data Streaming, also known as data in motion, implies the data which is movable or not at rest like data that has been seized and stockpiled in a database. Streaming Data is basically data that is generated unceasingly by myriads of data sources. Streaming data implies a wide variety of data such as data generated by the users through mobile phones or web applications, e-commerce purchases, various information from social media sites, geo-spatial services and many more.
Generally, this data needs to be processed consecutively and incrementally on a record-by-record basis and used for extensive analytics such as correlations, aggregations, computation, filtering, and sampling. Information which is obtained from such analysis gives companies a better insight which helps them in many aspects of their business and customer’s activity
Streaming data is applied in sectors like pharmaceutical research, energy production, capital markets and other fields where millions of transactions are generated through devices.
How is big data and data streaming related?
Data streams share a harmonious relation with Event Stream Processing(ESP) software. It is a key tool which has the capacity to process high-volume data. In today’s data-driven world, data is churning out from multifarious sources. Event Stream Processing techniques are applied by the experts so that they can get to know many new areas and get a better and wider insight. Whether the data is from social media sites, consumer electronics or other technological devices, ESP can give a detailed information about the data sources.
Depending on the viewpoint and perception, event streams can be considered as big data. Big data is driven by three characteristics and they are volume, variety and velocity. It is true that the formats of event data are varied like the devices and communication protocols. But when it is a single device, the data format is known, so streaming data invalidates of the Variety, one of the Vs of Big data. but in practice one need to standardize and normalize multiple formats when applications process various streams of data to answer questions. So, the other two Vs of big data are relevant to event streaming, as the process streams volumes of data and transmission speeds are very high almost the hundreds of thousands to millions of events per second. The advent of the Internet of things (IoT) has enhanced the usage of ESP. With IoT there will be escalating data as many things like cars, appliances and gadgets will generate more and continuous data about operations, activities and behaviours that never existed earlier.
Taking advantage of data streaming will surely help in reducing operating costs, improving product reliability and will optimize usage models. Companies that shy away from data streaming need to rethink on ESP as a viable technology that helps to sustain market growth.