The world of big data is filled with a multitude of different technologies, processes, and further buzzwords that could confuse even the best of us.
Fast data is one of those terms that seems simple on the surface, but is actually a variety of things in one.
In essence, fast data is the process of big data in real-time in order to gain instant insights and the ability to take action on trends, customer insight, and numerous other areas.
Fast data can also be referred to as high-velocity data, or real-time data.
The underlying goal of fast data is to quickly gather and mine structured and unstructured data so that action can be taken.
Fast data can come from a number of different source such as from sensors, machine-to-machine communications and wire data.
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The term has grown in popularity as technologies around the Internet of Things have continued to grow. It has also grown in importance to an increased desire from businesses to tap into data instantly so that they can act upon it right away.
Not all data needs to be acted upon instantly but it is necessary to identify what data should be looked at straight away and what can sit in a database or a data lake before it is analysed.
Self-service Business Intelligence and in-memory databases have helped to increase the attention given to fast data as vendors have been increasingly active in providing this capability to their users’.
Potential use cases for fast data include being used for smart grid applications that can analyse real-time electric power usage across thousands of locations. The benefit of this would be the ability to balance supply across the grid and to more efficiently meet demand in different geographical areas.
Fast data also has a potential use case with security for smart surveillance cameras. Its use would be able to combine fast data with predictive analytics to identify and flag potential security issues.
