Building Real–Time Analytics Systems : From Events to Insights with Apache Kafka and Apache Pinot

With this practical book, data engineers at organizations that use event-processing systems such as Kafka, Google Pub/Sub, and AWS Kinesis will learn how to analyze data streams in real time. The faster you derive insights, the quicker you can spot changes in your business and act accordingly.

Gain deep insight into real-time analytics, including the features of these systems and the problems they solve. With this practical book, data engineers at organizations that use event-processing systems such as Kafka, Google Pub/Sub, and AWS Kinesis will learn how to analyze data streams in real time. The faster you derive insights, the quicker you can spot changes in your business and act accordingly. In the first part of this book, author Mark Needham from StarTree provides an overview of the real-time analytics space and an understanding of what goes into building real-time applications. The second part offers a series of hands-on tutorials that show you how to combine multiple software products to build real-time analytics applications for an imaginary pizza delivery service. With this book, you will:Learn common architectures for real-time analyticsDiscover how event processing differs from real-time analyticsIngest event data from Apache Kafka into Apache PinotCombine event streams with static data using Kafka StreamsWrite real-time queries against event data stored in Apache PinotBuild a real-time dashboard, fraud detection pipeline, order tracking app, and anomaly detection systemLearn how organizations like Uber, Stripe, and Just Eat use real-time analytics