Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 55,04
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 55,86
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 55,96
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 56,73
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 121,05
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 135,41
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Librería: Majestic Books, Hounslow, Reino Unido
EUR 130,03
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 121,82
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Idioma: Inglés
Publicado por River Publishers Okt 2024, 2024
ISBN 10: 877004337X ISBN 13: 9788770043373
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 72,88
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware - This book addresses models and methods for designing and implementing Big Data Systems to support mixed and complex decision processes, giving special attention to BDWs as a way of efficiently storing and processing batch or streaming data for structured or semi-structured analytical problems.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 147,44
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 137,84
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 148,16
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EUR 80,84
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Añadir al carritoCondición: Sehr gut. Zustand: Sehr gut | Seiten: 314 | Sprache: Englisch | Produktart: Bücher | Big Data is a concept of major relevance in today's world, sometimes highlighted as a key asset for productivity growth, innovation, and customer relationship, whose popularity has increased considerably during the last years. Areas like smart cities, manufacturing, retail, finance, software development, environment, digital media, among others, can benefit from the collection, storage, processing, and analysis of Big Data, leveraging unprecedented data-driven workflows and considerably improved decision-making processes. The concept of a Big Data Warehouse (BDW) is emerging as either an augmentation or a replacement of the traditional Data Warehouse (DW), a concept that has a long history as one of the most valuable enterprise data assets. Nevertheless, research in Big Data Warehousing is still in its infancy, lacking an integrated and validated approach for designing and implementing both the logical layer (data models, data flows, and interoperability between components) and the physical layer (technological infrastructure) of these complex systems. This book addresses models and methods for designing and implementing Big Data Systems to support mixed and complex decision processes, giving special attention to BDWs as a way of efficiently storing and processing batch or streaming data for structured or semi-structured analytical problems.
EUR 80,84
Cantidad disponible: 1 disponibles
Añadir al carritoCondición: Sehr gut. Zustand: Sehr gut | Seiten: 314 | Sprache: Englisch | Produktart: Bücher | Big Data is a concept of major relevance in today's world, sometimes highlighted as a key asset for productivity growth, innovation, and customer relationship, whose popularity has increased considerably during the last years. Areas like smart cities, manufacturing, retail, finance, software development, environment, digital media, among others, can benefit from the collection, storage, processing, and analysis of Big Data, leveraging unprecedented data-driven workflows and considerably improved decision-making processes. The concept of a Big Data Warehouse (BDW) is emerging as either an augmentation or a replacement of the traditional Data Warehouse (DW), a concept that has a long history as one of the most valuable enterprise data assets. Nevertheless, research in Big Data Warehousing is still in its infancy, lacking an integrated and validated approach for designing and implementing both the logical layer (data models, data flows, and interoperability between components) and the physical layer (technological infrastructure) of these complex systems. This book addresses models and methods for designing and implementing Big Data Systems to support mixed and complex decision processes, giving special attention to BDWs as a way of efficiently storing and processing batch or streaming data for structured or semi-structured analytical problems.
EUR 183,10
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Añadir al carritoHardcover. Condición: Brand New. 284 pages. 9.75x6.75x1.00 inches. In Stock.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 184,65
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Añadir al carritoHardcover. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 207,00
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Big Data is a concept of major relevance in today's world, sometimes highlighted as a key asset for productivity growth, innovation, and customer relationship, whose popularity has increased considerably during the last years. Areas like smart cities, manufacturing, retail, finance, software development, environment, digital media, among others, can benefit from the collection, storage, processing, and analysis of Big Data, leveraging unprecedented data-driven workflows and considerably improved decision-making processes.The concept of a Big Data Warehouse (BDW) is emerging as either an augmentation or a replacement of the traditional Data Warehouse (DW), a concept that has a long history as one of the most valuable enterprise data assets. Nevertheless, research in Big Data Warehousing is still in its infancy, lacking an integrated and validated approach for designing and implementing both the logical layer (data models, data flows, and interoperability between components) and the physical layer (technological infrastructure) of these complex systems.This book addresses models and methods for designing and implementing Big Data Systems to support mixed and complex decision processes, giving special attention to BDWs as a way of efficiently storing and processing batch or streaming data for structured or semi-structured analytical problems.