Data Warehousing in the Age of Big Data

Author: Krish Krishnan
Publisher: Newnes
ISBN: 0124059201
Format: PDF, Mobi
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Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory. Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse. Learn how to leverage Big Data by effectively integrating it into your data warehouse. Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

Proceedings of the Fourth International Forum on Decision Sciences

Author: Xiang Li
Publisher: Springer
ISBN: 9811029202
Format: PDF, Kindle
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These conference proceedings focus on the topics of data-driven decision-making, stochastic decision-making, fuzzy decision-making and their applications in real-life problems. Beijing University of Chemical Technology organized IFDS2016, the 4th International Forum on Decision Sciences, with the theme “Data-Driven Decision-Making.” The proceedings collect 84 selected papers presenting cutting-edge modeling and solution methods and include numerous practical case studies, making it a valuable resource for students, researchers and practitioners working in the fields of decision science, operations research, management science and engineering.

Human Development and Interaction in the Age of Ubiquitous Technology

Author: Rahman, Hakikur
Publisher: IGI Global
ISBN: 1522505571
Format: PDF, Mobi
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The human condition is affected by numerous factors in modern society. In modern times, technology is so integrated into culture that it has become necessary to perform even daily functions. Human Development and Interaction in the Age of Ubiquitous Technology is an authoritative reference source for the latest scholarly research on the widespread integration of technological innovations around the globe and examines how human-computer interaction affects various aspects of people’s lives. Featuring emergent research from theoretical perspectives and case studies, this book is ideally designed for professionals, students, practitioners, and academicians.

C mo crear un data warehouse

Author: Curto Díaz, Josep
Publisher: Editorial UOC
ISBN: 8490648190
Format: PDF, Kindle
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¿Qué es H2PAC? El modelo H2PAC resuelve propuestas clave a partir de ACTIVIDADES. Esta forma de aprendizaje parte de un RETO: la actividad que deberás resolver. Para ello te facilitamos un contenido teórico, EL CONOCIMIENTO IMPRESCINDIBLE, que te ayudará a entender los conceptos esenciales para poder afrontar el desafío planteado inicialmente. Además del contenido teórico, el modelo también te facilita LAS SOLUCIONES, una propuesta de resolución del reto expuesto. Saber qué es un data warehouse (almacén de datos) y para qué sirve, o aprender a crear uno para analizar datos reales. El lector elegirá si ser un mero espectador, leyendo sobre almacenes de datos y viendo cómo se aplican en un problema real, o ser el actor principal, implementando él mismo el almacén de datos a partir del reto planteado y los datos facilitados.

Real Time Data Mining

Author: Florian Stompe
Publisher: Diplomica Verlag
ISBN: 3836678799
Format: PDF, Mobi
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Data Mining ist ein inzwischen etabliertes, erfolgreiches Werkzeug zur Extraktion von neuem, bislang unbekanntem Wissen aus Daten. In mittlerweile fast allen gr eren Unternehmen wird es genutzt um Mehrwerte f r Kunden zu generieren, den Erfolg von Marketingkampagnen zu erh hen, Betrugsverdacht aufzudecken oder beispielsweise durch Segmentierung unterschiedliche Kundengruppen zu identifizieren. Ein Grundproblem der intelligenten Datenanalyse besteht darin, dass Daten oftmals in rasanter Geschwindigkeit neu entstehen. Eink ufe im Supermarkt, Telefonverbindungen oder der ffentliche Verkehr erzeugen t glich eine neue Flut an Daten, in denen potentiell wertvolles Wissen steckt. Die versteckten Zusammenh nge und Muster k nnen sich im Zeitverlauf mehr oder weniger stark ver ndern. Datenmodellierung findet in der Regel aber noch immer einmalig bzw. sporadisch auf dem Snapshot einer Datenbank statt. Einmal erkannte Muster oder Zusammenh nge werden auch dann noch angenommen, wenn diese l ngst nicht mehr bestehen. Gerade in dynamischen Umgebungen wie zum Beispiel einem Internet-Shop sind Data Mining Modelle daher schnell veraltet. Betrugsversuche k nnen dann unter Umst nden nicht mehr erkannt, Absatzpotentiale nicht mehr genutzt werden oder Produktempfehlungen basieren auf veralteten Warenk rben. Um dauerhaft Wettbewerbsvorteile erzielen zu k nnen, muss das Wissen ber Daten aber m glichst aktuell und von ausgezeichneter Qualit t sein. Der Inhalt dieses Buches skizziert Methoden und Vorgehensweisen von Data Mining in Echtzeit.

On the Move to Meaningful Internet Systems OTM 2011

Author: Robert Meersman
Publisher: Springer Science & Business Media
ISBN: 3642251080
Format: PDF, ePub, Mobi
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The two-volume set LNCS 7044 and 7045 constitutes the refereed proceedings of three confederated international conferences: Cooperative Information Systems (CoopIS 2011), Distributed Objects and Applications - Secure Virtual Infrastructures (DOA-SVI 2011), and Ontologies, DataBases and Applications of SEmantics (ODBASE 2011) held as part of OTM 2011 in October 2011 in Hersonissos on the island of Crete, Greece. The 55 revised full papers presented were carefully reviewed and selected from a total of 141 submissions. The 27 papers included in the first volume constitute the proceedings of CoopIS 2011 and are organized in topical sections on business process repositories, business process compliance and risk management, service orchestration and workflows, intelligent information systems and distributed agent systems, emerging trends in business process support, techniques for building cooperative information systems, security and privacy in collaborative applications, and data and information management.

Big Data

Author: Kuan-Ching Li
Publisher: CRC Press
ISBN: 1498760406
Format: PDF, ePub, Mobi
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As today’s organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages. Presenting the contributions of leading experts in their respective fields, Big Data: Algorithms, Analytics, and Applications bridges the gap between the vastness of Big Data and the appropriate computational methods for scientific and social discovery. It covers fundamental issues about Big Data, including efficient algorithmic methods to process data, better analytical strategies to digest data, and representative applications in diverse fields, such as medicine, science, and engineering. The book is organized into five main sections: Big Data Management—considers the research issues related to the management of Big Data, including indexing and scalability aspects Big Data Processing—addresses the problem of processing Big Data across a wide range of resource-intensive computational settings Big Data Stream Techniques and Algorithms—explores research issues regarding the management and mining of Big Data in streaming environments Big Data Privacy—focuses on models, techniques, and algorithms for preserving Big Data privacy Big Data Applications—illustrates practical applications of Big Data across several domains, including finance, multimedia tools, biometrics, and satellite Big Data processing Overall, the book reports on state-of-the-art studies and achievements in algorithms, analytics, and applications of Big Data. It provides readers with the basis for further efforts in this challenging scientific field that will play a leading role in next-generation database, data warehousing, data mining, and cloud computing research. It also explores related applications in diverse sectors, covering technologies for media/data communication, elastic media/data storage, cross-network media/data fusion, and SaaS.