Real-time business intelligence (RTBI) refers to the continuous processing and analysis of streaming data to deliver immediate insights for decision-making. Unlike traditional BI, which operates on batch-processed historical data, RTBI systems ingest, transform, and visualize data within seconds or milliseconds of its generation, enabling organizations to respond instantly to changing conditions. The architecture combines event streaming platforms, in-memory processing, low-latency databases, and push-based delivery mechanisms. A critical mental model: real-time BI trades some consistency guarantees and implementation complexity for dramatically reduced data latency—understanding when this tradeoff creates business value versus unnecessary overhead is essential for successful implementation.
What This Cheat Sheet Covers
This topic spans 16 focused tables and 101 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: Core Architectural Patterns
| Pattern | Example | Description |
|---|---|---|
Batch layer + Speed layer + Serving layer | • Hybrid approach combining batch processing for accuracy with stream processing for low latency • batch layer recomputes complete views while speed layer provides real-time approximations. | |
Single stream processing path | • Simplified pattern using only streaming to avoid dual codebases • all data flows through an event log like Kafka and is processed once in real-time. | |
Microservices reacting to Kafka events | • Systems communicate through asynchronous event production and consumption • producers emit events to topics, consumers react independently without direct coupling. |