Event stream processing helps users study multiple never-ending event streams simultaneously to detect patterns or inspect results. These event streams may contain data about social media posts, emails, bank deposits, customer orders, or sensor data from vehicles, weather, or mobile devices. Unlike batch processing that requires data to first build up before being processed, stream processing can process data and events as they come in.
As stream processing software enables users to examine data changes in real-time or near real-time, a growing number of organizations are integrating platforms with this capability into their systems to make sound decisions faster.
Apache Kafka is one of those solutions, providing users with insights into trends and anomalies in data.
Event Streaming: A New Way to Monitor Data and Events
Stream processing applications like Kafka make it possible to transmit and react to data almost instantaneously. It’s a very practical tool, given that people produce at least 1.7 megabytes of data per second. What’s more, over 41 billion devices are expected to be connected to the Internet of Things by 2025.
Here are some common “data in motion” or real-time events:
· Page access
This refers to each time a user accesses a page. Information about the user, the page opened, and how the page was used can be recorded as part of an event.
Retailers and e-commerce marketers can use information about customer behavior gathered by event streaming platforms for context-aware advertising. Contextual marketing involves showing ads and promotional materials to online consumers based on their profile and location. Geofencing or location-based marketing for apps targeting vehicle owners follows the same principle.
· Data access
Uploading or transferring and exporting data count as events. For instance, events occur every time hospitals and health professionals update patient records on medical dashboards.
· Authentication and threat detection
Log-in and log-out events can indicate official or malicious entry (multiple log-in attempts) to an account. Also, a series of events can be identified as a security threat stream if they include abnormal activities that you’ve defined as constituting a breach or putting the system at risk.
In banking or trade, event stream platforms can monitor real-time payments and detect fraud or cybersecurity attacks.
How to Maximize Event Streams Using Kafka
To make Apache Kafka truly work for your business, you can examine the event streams that it processes in the following ways:
- Determine the “messages” you’re getting in terms of event patterns or trends.
- Check the speed by which you receive those messages.
- Analyze the generated metrics.
- Design informative and actionable alerts or notifications based on the results of your analytics.
Let BBI Help You Profit from Your Real-Time Data
Apache Kafka can be a valuable addition to your company’s digital assets when it comes to responding to extensive data in real-time. In today’s highly competitive business environment, this event-driven system’s speed and scalability are vital for rule-based alerting, anomaly detection, and customer satisfaction. Contact us today to find out how we can help you use Kafka’s real-time reporting and data pipelines to give your organization a winning edge.
