It’s estimated that by 2020 there will be over 50 billion connected devices, generating at least 11 Trillion dollars. With the exponential growth of connected "things," the volume of data to be analyzed will increase dramatically.
The traditional IT approach to data analytics has been to collect and store data, then analyze it. However, in an IoT context, this is not always desirable or practical, so new analytic architectures are emerging. Companies that can extracted meaningful content and knowledge quickly and efficiently will grow, the ones that are not able to harness all this data will wither away.
The benefits of analytics are too numerous to list, however there’s a new paradigm occurring in the traditional analytical ecosystem. The volumes and speed of data being created will soon make the current method of collecting data, storing it and analyzing it seem as quant at the punch card. It’s not enough having just a OLAP and a OLTP strategy, SQL vs NoSQL strategy, nor is it enough to have a Big Data strategy. The future will require a complete new paradigm, it will require an Edge Data strategy.
There’s a correlation between the length of time data is stored and the point it’s made actionable. Old data results in low relevancy, cloud IoT and the immediate demand for information makes this critical.
Edge Data is an extension of edge computing where applications, data and services are constantly being moved to the edge of an enterprises traditional data center. In an Edge Data centric architecture, all actionable “hot” data is either cached at the very edge of the network, as close to the producer or consumer of the data or processed at the instance its created, between the “things” themselves.
Edge Data architecture enables connected application to both utilize cloud based algorithms to make sense of the data in real time by utilizing Event Stream Processing (ESP) and edge databases, turning data into an actionable resource instantaneously. ESP is the process of quickly analyzing time-based data as it is being created and before it’s stored, even at the instant that it is streaming from one device to another. Which significantly accelerate the processing of data, created by all the “thinks” in Internet of Things, turning data into actionable events.
IoT is more than mobile and sensors located at the edge your network. Fundamentally it’s about making data actionable and relevant in real time. Enabling a deeper understanding of customer behavior to deliver tailored services, improve products and enable predictive analytics. Implementing a decentralized Edge Data strategy enables all this while delivering a more agile data management process, reducing enterprises overall infrastructure footprint and an moving enterprises toward a Serverless Architecture.