Streaming Data Mesh
A Model for Optimizing Real-Time Data Services
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Narrateur(s):
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Mike Lenz
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Auteur(s):
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Hubert Dulay
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Stephen Mooney
À propos de cet audio
Data lakes and warehouses have become increasingly fragile, costly, and difficult to maintain as data gets bigger and moves faster. Data meshes can help your organization decentralize data, giving ownership back to the engineers who produced it. This book provides a concise yet comprehensive overview of data mesh patterns for streaming and real-time data services.
Authors Hubert Dulay and Stephen Mooney examine the vast differences between streaming and batch data meshes. Data engineers, architects, data product owners, and those in DevOps and MLOps roles will learn steps for implementing a streaming data mesh, from defining a data domain to building a good data product. Through the course of the book, you'll create a complete self-service data platform and devise a data governance system that enables your mesh to work seamlessly.
With this book, you will design a streaming data mesh using Kafka; learn how to identify a domain; build your first data product using self-service tools; apply data governance to the data products you create; learn the differences between synchronous and asynchronous data services; and implement self-services that support decentralized data.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
©2023 Hubert Dulay and Stephen Mooney (P)2024 Ascent Audio