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Developers often view analytics as historical, sleepy and rearview-mirror analyses of data. But with streaming analytics, developers can build applications that can analyze and act on what's happening in business at this very moment.
These applications are built using real time streaming events/data. These real-time streaming events are typically called perishable insights, because they occur at a moment's notice and must be acted upon fast within a narrow window of opportunity before they quickly lose their value. Examples of such real time streaming data are high-velocity real-time data sources such as market data, Internet of Things (IOT), mobile, sensors, clickstream, and even high frequency transactions. Such high velocity real time data remains largely unutilized by most organizations.
But by using capabilities of streaming analytics, organizations can now easily perform real-time analytics on data that has been traditionally analyzed using batch processing in data warehouses or using Hadoop frameworks, and react to new information in minutes or seconds instead of hours or days.
In this webinar, I will discuss this prevalent trend of streaming analytics, its business significance, its technological components and why it will be prevalent in all future application development.
Varun Khandelwal
Varun Khandelwal is a Solution Architect for Analytics (MENA and India region) with Bahwan Cybertek. Through thought leadership and customer engagement, he helps businesses remain competitive in the ever-changing digital landscape. He has worked in many industries such as Financial Services, Energy, Life Sciences, Media & Networks, Consumer Goods & Retail, and Telco to address business problems in analytics domain. Over the period of years he has developed deep experience in analytics and optimization area. He also works as a technology evangelist to spread the Analytics/Data Science knowledge across partners, customers and data science community.
Varun is a speaker at DataHack Summit 2019, India’s most advanced conference on machine learning and artificial intelligence.
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