July 16, 2024

Vernita Llorca

High Tech Security

The Ultimate Guide To Real-Time Data Processing

4 min read
The Ultimate Guide To Real-Time Data Processing


What is real-time processing? It’s the ability to use data as soon as it’s produced, rather than waiting for an analysis engine to crunch through it first. Real-time processing can be used in many ways, such as detecting fraud or identifying trends. In this guide, we’ll look at what real-time processing is and how you can use it in your own business.


You’ve probably heard the term “real-time data processing” before. But what does it really mean? And why is it important to your business?

Real-time means that information is analyzed and acted upon as soon as possible–in other words, without any delay. It’s different from batch processing because there isn’t any waiting around for batches to be completed before you can start analyzing your data and making decisions based on those analyses. Instead, real-time systems allow you to process each individual piece of incoming information as soon as it arrives so that you don’t have to wait for all of them together at once (which would take much longer).

The Ultimate Guide To Real-Time Data Processing

Types of real-time processing

Real-time processing is a category of data processing that occurs in near real-time. It differs from batch processing in that it can handle large volumes of data in a very short period of time, while still maintaining the same level of accuracy and reliability as batch processing.

Real-time applications can be divided into three categories: stream processing, event driven architectures (EDA), and hybrid systems.

Types of data sources for real-time analytics

Real-time data processing is the act of analyzing and responding to live data as it’s being generated. In this guide, we’ll take a look at some of the different types of sources you can use to collect real-time data.

  • Web Data: The web is home to a vast array of information, from social media posts to news articles and more–and all that content can be used for real-time analytics purposes! It’s important to remember that not all web content will be available for immediate analysis; some sites require users sign in before accessing certain pages or information (like Facebook), while others may restrict access based on location or device type (like Netflix). However, there are still plenty of opportunities out there if you know where and how to look for them!

Business cases for real-time processing

Business cases for real-time processing include:

  • Getting more from your data. Real-time processing can help you get more value out of the data you already have by making it easier to access and analyze. You may be able to find new insights that would otherwise have been overlooked, or use historical information in new ways. For example, if a company has been collecting customer transaction history but hasn’t been analyzing it until now, they could use this information to optimize sales strategies or predict customer behavior based on past purchases (and then act on those predictions). This could help them increase revenue by improving customer experiences and reducing costs at the same time!
  • Making better decisions faster with real-time analysis tools like Apache Spark streaming engine which enables developers with minimal knowledge about distributed systems development paradigms such as MapReduce/Hadoop framework so they can focus on writing reusable code instead having reinventing wheels every time there’s an issue with some existing technology stack due lack of documentation available online nowadays.”

Models for real-time processing

Real-time processing is not a new concept. It’s been around for years, but it’s become increasingly popular as businesses have grown increasingly data-driven.

Real-time processing can be thought of as an alternative to batch processing, where you run your analytics once at night or over the weekend instead of continuously throughout the day. Real-time processing allows you to analyze data in real time so that you can make decisions based on current events rather than historical ones.

For example: You want to know how many people are visiting your website right now? You could set up an alarm that sends an email every hour with this information during business hours (the “batch” part), or alternatively you could use some kind of service that monitors traffic on your site in real time (the “real” part).

Real-time processing can help you get more from your data.

Real-time processing is a way to get more from your data. You can use it to improve business processes and customer experience, make better decisions, and be more competitive.

In this article we’ll look at the benefits of real-time processing, explain what it is and how it works, then show you how to put together a real-time data pipeline using StreamSets Data Collector (a free open source tool) with Amazon Kinesis Firehose.


Real-time data processing can be a powerful tool for business analytics. It allows you to get more from your data and make faster, better decisions. If you’re interested in learning more about real-time processing or want help setting up an implementation plan for your organization, please contact us today!

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