Compendium admissions 2023-25



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PI Prep Kit 2023
Further Reading –
● What is DevOps - Explained | New Relic
● What is DevOps? - DevOps.com
● What is DevOps? DevOps Explained | Microsoft Azure

Industry 4.0
Industry 4.0 refers to anew phase in the Industrial Revolution that focuses heavily on interconnectivity, automation, machine learning, and real-time data. It is commonly known as the fourth industrial revolution.


125 Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and AI and machine learning, into their production facilities and throughout their operations. Analyzing the large amounts of big data collected from sensors on the factory floor ensures real-time visibility of manufacturing assets. Industry 4.0 concepts and technologies can be applied across all types of industrial companies, including discrete and process manufacturing, as well as oil and gas, mining, and other industrial segments. https://manufacturingglobal.com/smart-manufacturing/what-industry-40
Edge Computing
Edge computing is a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers. This proximity to data at its source can deliver strong business benefits faster insights, improved response times, and better bandwidth availability.
Why edge computing
The promise of cloud and AI was to automate and speed innovation by driving actionable insight from data. But the unprecedented scale and complexity of data that are created by connected devices have outpaced network and infrastructure capabilities. Sending all that device-generated data to a centralized data center or to the cloud causes bandwidth and latency issues. Edge computing offers a more efficient alternative data is processed and analyzed closer to the point where it's created. Because data does not traverse over a network to a cloud or data center to be processed, latency is significantly reduced. Edge computing — and mobile edge computing on G networks
— enables faster and more comprehensive data analysis, creating the opportunity for deeper insights, faster response times, and improved customer experiences.

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