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Название: Building Real-Time Analytics Systems: From Events to Insights with Apache Kafka and Apache Pinot (5th Early Release)
Автор: Mark Needham
Издательство: O’Reilly Media, Inc.
Год: 2023-04-27
Страниц: 111
Язык: английский
Формат: epub
Размер: 10.1 MB
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. The term “streaming” describes a continuous, never-ending flow of data with no beginning or end. The data is made available incrementally over time, which means that you can act upon it without needing to download everything in one go. A data stream consists of a series of data points ordered in time. Each data point represents an “event” or a change in state that has occurred in the business. For example, a customer purchasing a product becomes an event, which captures facts about the person, product, price, and transaction time.
Автор: Mark Needham
Издательство: O’Reilly Media, Inc.
Год: 2023-04-27
Страниц: 111
Язык: английский
Формат: epub
Размер: 10.1 MB
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. The term “streaming” describes a continuous, never-ending flow of data with no beginning or end. The data is made available incrementally over time, which means that you can act upon it without needing to download everything in one go. A data stream consists of a series of data points ordered in time. Each data point represents an “event” or a change in state that has occurred in the business. For example, a customer purchasing a product becomes an event, which captures facts about the person, product, price, and transaction time.