China has been headline news since the announcement of the Covid-19 outbreak early this year. While much of it hinges on its management of the pandemic, another event that has been running parallely is the clarion call to ban tech engagements with the country.
For decades, the Indian Railways has been a significant and sole way for commutation in the country. Being the third-largest railway network in the world by size, it accommodates and offers its services to people from all walks of life.
With that being said, such a mammoth size of the railway system needs several aspects of the working to align for the system to function smoothly. And, even the slightest of disruption in the network can create hassle in the schedule, creating inconvenience to lakhs of people. Thus, to make the running of the system run smoother, there was a requirement for Indian Railways to deploy a consolidated system that runs on automation to get the job done in real-time.
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Agrochemical companies manufacture a range of offerings for yield maximisation, pest resistance, hardiness, water quality and availability and other challenges facing farmers. These companies need to measure the efficacy of their products in real-world conditions, not just controlled experimental environments. Single-crop farms are divided into plots and a specific intervention performed in each. For example, hybrid seeds are sown in one plot while another is treated with fertilisers, and so on. The relative performance of each treatment is assessed by tracking the plants’ health in the plot where that treatment was administered.
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The overnight transformation of companies adopting new technologies and transitioning to a digital work environment amid pandemic has made upskilling the most critical component in a worker’s repertoire in 2021. While information, data and the ability to make the right decisions serve as a stabiliser across verticals, analytics and data science have become indispensable tools to navigate today’s career scene.
According to a recent Forrester study, the top two challenges decision-makers cited are — the lack of employees with data skillsets and the lack of skills among business users who must use data insights. Almost 66% of organisations believe there is a requirement for data literacy among employees, where 59% demand analytic efficiency. However, with a converged approach to analytics through democratising access to data, automating tedious and complex processes, and promoting upskilling of data and knowledge workers, organisations can create a thriving data and analytics culture within.
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More and more mobile applications are utilizing power WebView to customize the user experience on runtime. And it is all the more important to track users’ activities on the WebView.
However, Firebase analytics’s SDK doesn’t support sending events from WebView pages of the mobile app. So to use Analytics in WebView, its events must be forwarded to native code before they can be sent to analytics.
First, we have to pass the events from WebView to native code.
Second, fetch the passed events in the native environment and send it to Firebase Analytics.
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The proliferation of big data analytics solutions has significantly redefined businesses’ data processing over the years. It has already proven a key solution for identifying and deriving meaningful insights from vast datasets. With emerging technologies like artificial intelligence, machine learning and the cloud, data professionals are now leveraging cognitive analytics to drive real-time decision making. It presents much greater potential than big data analytics, unlocking the value of big data by making a system more self-reliant, and information contained more accessible.
Since data is considered the oil of today’s digital economy, data analytics is an indispensable economic driver. Over the years, it has evolved exponentially including from descriptive to diagnostic and predictive to prescriptive. Cognitive analytics is now likely to become the next frontier of this data analytics trend. It exploits high-performance computing power by integrating artificial intelligence and machine learning techniques with data analytics approaches.
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