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Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and;
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Organizations invest incredible amounts of time and money obtaining and then storing big data in data stores called data lakes. But how;
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Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a;
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As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer;
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This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The;
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This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The;
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This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term Big Data;
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Get started with Azure Synapse Analytics, Microsoft's modern data analytics platform. This book covers core components such as Synapse SQL;
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Learn how to integrate full-stack open source big data architecture and to choose the correct technology-Scala/Spark, Mesos, Akka;
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, including how to incorporate business architecture, information architecture, data architecture, application (software) architecture together to;
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Data Modeling for Agile Data Warehouse using Data Vault Modeling Approach. Includes Enterprise Data Warehouse Architecture. This is a;
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Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software;
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DW 2.0: The Architecture for the Next Generation of Data Warehousing is the first book on the new generation of data warehouse;
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A practical guide to implementing your enterprise data lake using Lambda Architecture as the base About This Book * Build a full;
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Data as a Service shows how organizations can leverage data as a service by providing real-life case studies on the various and innovative;
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This book constitutes the refereed proceedings of the First Workshop on Big Scientific Data Benchmarks, Architecture, and Systems, SDBA;
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This book is an essential read for Data Architects or indeed anyone wanting to improve the benefit that their organisation can derive from;
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in their organization. You will learn Salesforce architecture: solution architecture, data architecture, security architecture, integration;
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machine structure. This book explains the forces behind this convergence of shared-memory, message-passing, data parallel, and data-driven;
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Pop the hood on SAP S/4HANA with this guide to its technical and application architecture! Understand the new data and programming models;
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Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply;
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Combine the incredible powers of Spark, Mesos, Akka, Cassandra, and Kafka to build data processing platforms that can take on even the;
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model independent of organizational boundaries, systems, and procedures, aeo define data before application, and aeo let data determine the;
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Mattison explains what data warehouses are and how they work, key concepts of business reengineering, client/server technology, systems;
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industrial customers in the past decade. It presents context factors, empirical data, and example cases, as well as lessons learned on mitigating the;
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