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Real-time applications are becoming the norm today. But building a model that works properly requires real-time data from the source, in-flight stream processing, and low latency serving of its analytics. With this practical book, data engineers, data architects, and data analysts will learn how to use streaming databases to build real-time solutions. Authors Hubert Dulay and Ralph M. Debusmann take you through streaming database fundamentals, including how these databases reduce infrastructure for real-time solutions. You'll learn the difference between streaming databases, stream processing, and real-time online analytical processing (OLAP) databases. And you'll discover when to use push queries versus pull queries, and how to serve synchronous and asynchronous data emanating from streaming databases. This guide helps you: Explore stream processing and streaming databases Learn how to build a real-time solution with a streaming database Understand how to construct materialized views from any number of streams Learn how to serve synchronous and asynchronous data Get started building low-complexity streaming solutions with minimal setup
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 Implement self-services that support decentralized data
Real-time applications are becoming the norm today. But building a model that works properly requires real-time data from the source, in-flight stream processing, and low latency serving of its analytics. With this practical book, data engineers, data architects, and data analysts will learn how to use streaming databases to build real-time solutions. Authors Hubert Dulay and Ralph M. Debusmann take you through streaming database fundamentals, including how these databases reduce infrastructure for real-time solutions. You'll learn the difference between streaming databases, stream processing, and real-time online analytical processing (OLAP) databases. And you'll discover when to use push queries versus pull queries, and how to serve synchronous and asynchronous data emanating from streaming databases. This guide helps you: Explore stream processing and streaming databases Learn how to build a real-time solution with a streaming database Understand how to construct materialized views from any number of streams Learn how to serve synchronous and asynchronous data Get started building low-complexity streaming solutions with minimal setup
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. 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 book's 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. You will: Learn common architectures for real-time analytics Discover how event processing differs from real-time analytics Ingest event data from Apache Kafka into Apache Pinot Combine event streams with OLTP data using Debezium and Kafka Streams Write real-time queries against event data stored in Apache Pinot Build a real-time dashboard and order tracking app Learn how Uber, Stripe, and Just Eat use real-time analytics
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The Essence of Chromatography presents a comprehensive survey of modern chromatography and is intended as a suitable text for graduate level courses in the separation sciences and as a self-study guide for professional chromatographers wishing to refresh their background in this rapidly expanding field.This title is an effective replacement for Chromatography Today, written by the same author with Salwa K. Poole, which is considered to be one of the definitive chromatographic texts of the last decade. Its format is modular, with extensive cross-references to permit rapid location of re.
This book brings together papers that discuss social and structural aspects of language contact and language change. Several papers look at the relevance of historical documents to determine the linguistic nature of early contact varieties, while others investigate the specific processes of contact-induced change that were involved in the emergence and development of these languages. A third set of papers look at how new datasets and greater sensitivity to social issues can help to (re)assess persistent theoretical and empirical questions as well as help to open up new avenues of research. In particular they highlight the heterogeneity of contemporary language practices and attitudes often obscured in sociolinguistic research. The contributions all focus on language variation and change but investigate it from a variety of disciplinary and empirical perspectives and cover a range of linguistic contexts.
Summary Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology As humans, we're constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent a...