More and more major companies are realizing the full value of having real-time data-driven analytics at their fingertips. Everything from temperature sensor tracking and machinery wear-and-tear to social media metrics and targeted online searches to fraud and forecast trends can be critical information to a successful modern business.
In light of this, organizations have been turning en masse to Apache Kafka, and with good reason, as it’s just about the perfect tool for integrating these wildly diverse streams of real-time data across multiple, connected applications to improve decision-making.
However, many businesses still have not been able to take advantage of the benefits of the “real-time” aspect of these analytics.
The Problem with Kafka: Accessing Real-Time Information
Whether it’s an analyst doing reports or a data scientist applying machine learning methods to the data, they’re usually viewing it in aggregate from a traditional database, and typically don’t get to interact with it in its natural and most useful form—real-time.
The issue behind accessing real-time data is that most business intelligence, data science, and data management tools do not natively connect to Kafka. This means that getting useful analytical insights from Kafka usually requires custom coding as well as several complex components that are expensive, difficult, and time-consuming to implement.
Introducing TIBCO Cloud Data Streams for Kafka
But now, with TIBCO Cloud™ Data Streams, we’ve taken the expensive, custom-coding headache out of making that Kafka connection. Business users can just connect TIBCO Spotfire® software to Kafka messages and go.
With a native low-code, or, in most cases, no-code Kafka connection from TIBCO, analytics agility can be achieved in just minutes. Now, there’s nothing to stop you from taking advantage of what Kafka’s real-time analytics has to offer.
When TIBCO and Kafka Work Together, Businesses Win
As Kafka adoption becomes more widespread, the massive advantage in the practical application of real-time analytics continues to grow increasingly evident. Some recent use cases include:
- Real-time Monitoring of Sporting Events: TXODDS, a real-time aggregator and distributor of sports betting information, absorbs data from systems monitoring thousands of live sporting events in real-time, using a network of Kafka messages. The messages carry real-time inputs, such as which players are on the field, the score, and even the weather. These messages are fed to the TIBCO-powered TXODDS “brain,” which can compare current game conditions to history, execute sophisticated artificial intelligence (AI) learning models to predict which way the game is likely to go based on in-game data, and transmit a stream of data and predictions to their subscribers.
- Predictive Global Bank Operations: A top-tier financial institution uses TIBCO to monitor global trading activity and get a real-time view of the impact of client orders, trading activity, and IT infrastructure all at once. Based on Kafka messages, the bank has predictive operations that can spot and stop problems before they happen, increasing agility and requiring fewer resources for citizen developers.
- Near-Instant Fraud Detection: Another well-known bank is using Kafka and TIBCO to detect credit risk in real-time without any human intervention. Credit card scans are captured as real-time triggered events that stream through Kafka. The system learns what a fraud-like transaction looks like and makes an autonomous decision based on its learnings.
By building a bridge between open-source developers and business users, TIBCO helps you come together as a team to manage Kafka-powered business systems.
To learn how to analyze Kafka data in minutes, download this ebook “How to Easily Get Real-time Analytics from Kafka.”