Artificial Intelligence and Data Analytics are applied in almost every industry today. They are now being applied to the Indian Railways as well. In this week’s guide, we will talk about how data analytics can be used for operational efficiency. We will also learn more about whether edge analytics is the future of real-time analytics.
Piyush Goyal, in bid to improve the operational efficiency of Indian Railways, has said that they are all set to go big with data analytics and artificial intelligence. There has been a tie-up with the Indian School of Business in Hyderabad to analyse and derive insights from the data that is generated by the Indian Railways. The chairman of the railway board, V K Yadav, has said that a centre for excellence will be set up within the coming three months. Data regarding the train operations, passengers, freight, assets are available, and this data should be analysed with the help of data analytics to help in improving the efficiency of the services and to predict asset maintenance as well.
ISB has already been given the responsibility of planning an introductory capacity building program. 88 officials are already in the process of being trained in areas such as data science, big data analytics, AI, reinforcement learning and cloud computing over the last two months. Such training will be given to every zone.
Is Edge Analytics the future of Real-time analytics?
Before we move on to understanding whether edge analytics is the future, let us take a look at what it means. A data analytics model wherein the incoming data is analysed at a non-central point is known as Edge Analytics. It takes place near a sensor, a network switch, or any other connected device. Due to its decentralised nature, one of the main benefits of edge analytics is that it is faster, leads to quick and more accurate business intelligence when compared to traditional methods. It also poses a lighter load on the network.
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