Data Streams

Data Streams is a powerful feature that allows real-time access to raw data from Mapp Intelligence, enabling immediate insights from end-user interactions. Unlike traditional batch data delivery, Data Streams continuously provide a flow of events, allowing you to capture user actions on your website or app as they happen.

Key Features

• Real-Time Insights: Data Streams capture and deliver events instantly, offering real-time visibility into user interactions.

• Event-Based Data: Events represent the most granular level of user actions, including page views and other interactions, with detailed attributes that help define and analyze user behavior.

• Scalable Technology: Built on Apache Kafka, a leading industry-standard messaging system known for its scalability, reliability, and speed, ensuring access to processed Mapp Intelligence data within seconds.

Event Granularity

Events are the core of Data Streams, representing the smallest unit of user interaction. While you can define events at any granularity, the lowest level typically provides the most accurate representation of your business needs.

Technical Background

Mapp’s Data Streams use a standard Apache Kafka setup, delivering a robust, scalable, and high-performance system. For more detailed technical guidance and best practices on Kafka, refer to the official Apache Kafka documentation.

Additional Resources

This documentation will guide you through the introduction, implementation, and basic troubleshooting of Data Streams. Where applicable, we provide links to relevant external resources for specific Kafka configuration details.