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Real-time Streaming And Analytics Use Cases
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Real-time Streaming Use Cases. How Does It Help Business?

Real-time streaming tools and techniques hold high potential in the decision-making and operations of an organization. Modern businesses are dependent on thousands of applications that generate, collect, process, and analyze data continuously. In this article we will talk about some use cases of real time streaming & analytics and its benefits to the businesses.

Since the advent of the Internet of things, the number of interconnected devices has been on the rise. A report estimates there will be 24.1 billion connected devices by 2030. While this number glorifies how well businesses are willing to embrace technological change, it also foreshadows the amount of data that will be generated.

Benefits of Real-time Streaming and Analytics For businesses

The real-time data streaming tools and techniques benefit businesses to improve their overall productivity, optimize their resources and enhance customer experience. Here’s how:

●       Reflects real-time changes in business :

Real-time data streaming using Kafka and analytics help in creating data visualizations that publish real-time changes within the company. These also help in creating interactive, customized, and accurate dashboards. It makes sharing of relevant data with stakeholders an easy-to-do task.

●       Facilitates real-time testing:

Event streams in action let businesses test for possible risks in real-time. It helps you understand and rectify potential issues that may arise while implementing new software or business processes.

●       Understands customer behavior:

Real-time data streaming gives insights into customer behavior and lets businesses gauge their reaction. With this knowledge, companies can implement policies or create required product changes to improve the brand’s customer experience.

●       Saves time and money:

As dashboards become shareable and interactive, authorized people across the organization can have access to it. It reduces the IT team’s burden, improves productivity, and ultimately saves time and money.

What Is Real-time Analytics, And Why Is It Gaining Popularity?

Businesses are now experiencing a paradigm shift from batch processing to real-time streaming to improve their capability to understand customer trends and address market changes on time. In the context of social media, a real-time streaming example could be

Real-time analytics is a technique where real-time data is analyzed and processed to generate actionable decisions or alerts that make up for the guiding light for decision-makers of an organization. Real-time analytics uses logic and mathematics to analyze real-time data and derive value out of it.

A Gartner report predicts that more than 50% of the new business would use real-time context data for faster and better decision-making processes by 2022. For companies to leverage real-time data without getting lost in the shuffle of numerous amounts of data it generates or absorbs, real-time analytics plays a crucial role.

 

Real time data streaming examples

 

 

Real-time Streaming and Analytics- Use Cases

Real-time data streaming uses event streaming in action to process data in motion rather than that in rest. Some of the ways organizations are tapping the wonderfulness of real-time data analytics are:

●       Information security

One of the most potent ways to use real-time data analytics is in supporting organizations with better data security measures. Real-time data analytics allows to aggregate data and analyze activities in real-time.

●       Real-time Marketing

Real-time customer analytics play a crucial role in enhancing customer experience and implementing customer-focused marketing strategies. Around 44% of enterprises that leveraged real-time analytics to create customer-centric marketing could acquire new customers and increase their revenue.

●       Finance services

Finance frauds are one of the risks that have come along with the benefits of the digital revolution. Real-time data streaming Kafka has helped businesses to create a system that identifies such fraudulent cases on time. Companies also use it for chalking out safe and effective trade strategies.

 

Conclusion

Real-time data streaming using Kafka helps businesses across the globe to embrace new-age data-driven technologies. The analytics add value to the real-time data streams that benefit organizations to boost their profits by leaps and bounds.

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