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Data Lakes
by Anne Laurent Dominique Laurent Cédrine MaderaThe concept of a data lake is less than 10 years old, but they are already hugely implemented within large companies. Their goal is to efficiently deal with ever-growing volumes of heterogeneous data, while also facing various sophisticated user needs. However, defining and building a data lake is still a challenge, as no consensus has been reached so far. Data Lakes presents recent outcomes and trends in the field of data repositories. The main topics discussed are the data-driven architecture of a data lake; the management of metadata – supplying key information about the stored data, master data and reference data; the roles of linked data and fog computing in a data lake ecosystem; and how gravity principles apply in the context of data lakes. A variety of case studies are also presented, thus providing the reader with practical examples of data lake management.
Data Lakes For Dummies
by Alan R. SimonTake a dive into data lakes “Data lakes” is the latest buzz word in the world of data storage, management, and analysis. Data Lakes For Dummies decodes and demystifies the concept and helps you get a straightforward answer the question: “What exactly is a data lake and do I need one for my business?” Written for an audience of technology decision makers tasked with keeping up with the latest and greatest data options, this book provides the perfect introductory survey of these novel and growing features of the information landscape. It explains how they can help your business, what they can (and can’t) achieve, and what you need to do to create the lake that best suits your particular needs. With a minimum of jargon, prolific tech author and business intelligence consultant Alan Simon explains how data lakes differ from other data storage paradigms. Once you’ve got the background picture, he maps out ways you can add a data lake to your business systems; migrate existing information and switch on the fresh data supply; clean up the product; and open channels to the best intelligence software for to interpreting what you’ve stored. Understand and build data lake architecture Store, clean, and synchronize new and existing data Compare the best data lake vendors Structure raw data and produce usable analytics Whatever your business, data lakes are going to form ever more prominent parts of the information universe every business should have access to. Dive into this book to start exploring the deep competitive advantage they make possible—and make sure your business isn’t left standing on the shore.
Data Lakes For Dummies
by Alan R. SimonTake a dive into data lakes “Data lakes” is the latest buzz word in the world of data storage, management, and analysis. Data Lakes For Dummies decodes and demystifies the concept and helps you get a straightforward answer the question: “What exactly is a data lake and do I need one for my business?” Written for an audience of technology decision makers tasked with keeping up with the latest and greatest data options, this book provides the perfect introductory survey of these novel and growing features of the information landscape. It explains how they can help your business, what they can (and can’t) achieve, and what you need to do to create the lake that best suits your particular needs. With a minimum of jargon, prolific tech author and business intelligence consultant Alan Simon explains how data lakes differ from other data storage paradigms. Once you’ve got the background picture, he maps out ways you can add a data lake to your business systems; migrate existing information and switch on the fresh data supply; clean up the product; and open channels to the best intelligence software for to interpreting what you’ve stored. Understand and build data lake architecture Store, clean, and synchronize new and existing data Compare the best data lake vendors Structure raw data and produce usable analytics Whatever your business, data lakes are going to form ever more prominent parts of the information universe every business should have access to. Dive into this book to start exploring the deep competitive advantage they make possible—and make sure your business isn’t left standing on the shore.
Data Made Flesh: Embodying Information
by Robert Mitchell Phillip ThurtleIn an age of cloning, cyborgs, and biotechnology, the line between bodies and bytes seems to be disappearing. Data Made Flesh is the first collection to address the increasingly important links between information and embodiment, at a moment when we are routinely tempted, in the words of Donna Haraway, "to be raptured out of the bodies that matter in the lust for information," whether in the rush to complete the Human Genome Project or in the race to clone a human being.
Data Made Flesh: Embodying Information
by Robert Mitchell Phillip ThurtleIn an age of cloning, cyborgs, and biotechnology, the line between bodies and bytes seems to be disappearing. Data Made Flesh is the first collection to address the increasingly important links between information and embodiment, at a moment when we are routinely tempted, in the words of Donna Haraway, "to be raptured out of the bodies that matter in the lust for information," whether in the rush to complete the Human Genome Project or in the race to clone a human being.
Data Management: Der Weg zum datengetriebenen Unternehmen
by Klaus-Dieter GronwaldDieses Lehrbuch betrachtet Data Management als interdisziplinäres Konzept mit Fokus auf den Zielen datengetriebener Unternehmen. Im Zentrum steht die interaktive Entwicklung eines Unternehmensdatenmodells für ein virtuelles Unternehmen mit Unterstützung eines online Learning Games unter Einbeziehung der Aufgaben, Ziele und Grundsätze des Data Managements, typischer Data-Management-Komponenten und Frameworks wie Datenmodellierung und Design, Metadaten Management, Data Architecture, und Data Governance, und verknüpft diese mit datengetriebenen Anwendungen wie Business Warehousing, Big Data, In-Memory Data Management, und Machine Learning im Data Management Kontext.Das Buch dient als Lehrbuch für Studierende der Informatik, der Wirtschaft und der Wirtschaftsinformatik an Universitäten, Hochschulen und Fachschulen und zur industriellen Aus- und Weiterbildung.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2019, Volume 2 (Advances in Intelligent Systems and Computing #1016)
by Valentina Emilia Balas Amlan Chakrabarti Neha SharmaThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2018, Volume 1 (Advances in Intelligent Systems and Computing #808)
by Valentina Emilia Balas Neha Sharma Amlan ChakrabartiThe book presents the latest, high-quality, technical contributions and research findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It discusses state-of-the-art topics as well as the challenges and solutions for future development. It includes original and previously unpublished international research work highlighting research domains from different perspectives. This book is mainly intended for researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2018, Volume 2 (Advances in Intelligent Systems and Computing #839)
by Valentina Emilia Balas Neha Sharma Amlan ChakrabartiThe volume on Data Management, Analytics and Innovations presents the latest high-quality technical contributions and research results in the areas of data management and smart computing, big data management, artificial intelligence and data analytics along with advances in network technologies. It deals with the state-of-the-art topics and provides challenges and solutions for future development. Original, unpublished research work highlighting specific research domains from all viewpoints are contributed from scientists throughout the globe. This volume is mainly designed for professional audience, composed of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2022 (Lecture Notes on Data Engineering and Communications Technologies #137)
by Alfred M. Bruckstein C. Mohan Saptarsi Goswami Inderjit Singh Barara Amol GojeThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at Sixth International Conference on Data Management, Analytics and Innovation (ICDMAI 2022), held virtually during January 14–16, 2022. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2019, Volume 1 (Advances in Intelligent Systems and Computing #1042)
by Neha Sharma Amlan Chakrabarti Valentina Emilia BalasThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2021, Volume 1 (Lecture Notes on Data Engineering and Communications Technologies #70)
by Neha Sharma Amlan Chakrabarti Valentina Emilia Balas Alfred M. BrucksteinThis book presents the latest findings in the areas of data management and smart computing, machine learning, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at Fifth International Conference on Data Management, Analytics and Innovation (ICDMAI 2021), held during January 15–17, 2021, in a virtual mode. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2021, Volume 2 (Lecture Notes on Data Engineering and Communications Technologies #71)
by Neha Sharma Amlan Chakrabarti Valentina Emilia Balas Alfred M. BrucksteinThis book presents the latest findings in the areas of data management and smart computing, machine learning, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at Fifth International Conference on Data Management, Analytics and Innovation (ICDMAI 2021), held during January 15–17, 2021, in a virtual mode. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2020, Volume 1 (Advances in Intelligent Systems and Computing #1174)
by Neha Sharma Amlan Chakrabarti Valentina Emilia Balas Jan MartinovicThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17–19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2020, Volume 2 (Advances in Intelligent Systems and Computing #1175)
by Neha Sharma Amlan Chakrabarti Valentina Emilia Balas Jan MartinovicThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17–19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2023 (Lecture Notes in Networks and Systems #662)
by Neha Sharma Amol Goje Amlan Chakrabarti Alfred M. BrucksteinThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. The volume is a collection of peer reviewed research papers presented at Seventh International Conference on Data Management, Analytics and Innovation (ICDMAI 2023), held during 20 – 22 January, 2023 in Pune, India. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Data Management and Analysis: Case Studies in Education, Healthcare and Beyond (Studies in Big Data #65)
by Reda Alhajj Mohammad Moshirpour Behrouz FarData management and analysis is one of the fastest growing and most challenging areas of research and development in both academia and industry. Numerous types of applications and services have been studied and re-examined in this field resulting in this edited volume which includes chapters on effective approaches for dealing with the inherent complexity within data management and analysis. This edited volume contains practical case studies, and will appeal to students, researchers and professionals working in data management and analysis in the business, education, healthcare, and bioinformatics areas.
Data Management and Analytics for Medicine and Healthcare: Third International Workshop, DMAH 2017, Held at VLDB 2017, Munich, Germany, September 1, 2017, Proceedings (Lecture Notes in Computer Science #10494)
by Edmon Begoli, Fusheng Wang and Gang LuoThis book constitutes the thoroughly refereed conference proceedings of the Third International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2017, in Munich, Germany, in September 2017, held in conjunction with the 43rd International Conference on Very Large Data Bases, VLDB 2017. The 9 revised full papers presented together with 2 keynote abstracts were carefully reviewed and selected from 16 initial submissions. The papers are organized in topical sections on data privacy and trustability for electronic health records; biomedical data management and Integration; online mining of Health related data; and clinical data analytics.
Data Management and Analytics for Medicine and Healthcare: Second International Workshop, DMAH 2016, Held at VLDB 2016, New Delhi, India, September 9, 2016, Revised Selected Papers (Lecture Notes in Computer Science #10186)
by Fusheng Wang Lixia Yao Gang LuoThis book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2016, in New Delhi, India, in September 2016, held in conjunction with the 42nd International Conference on Very Large Data Bases, VLDB 2016. The 7 revised full papers presented together with 2 invited papers and 3 keynote abstracts were carefully reviewed and selected from 11 initial submissions. The papers are organized in topical sections on knowledge discovery of biomedical data; managing, querying and processing of medical image data; information extraction and data integration for biomedical data; and health information systems.
Data Management and Internet Computing for Image/Pattern Analysis (The International Series on Asian Studies in Computer and Information Science #11)
by David D. Zhang Xiaobo Li Zhiyong LiuData Management and Internet Computing for Image/Pattern Analysis focuses on the data management issues and Internet computing aspect of image processing and pattern recognition research. The book presents a comprehensive overview of the state of the art, providing detailed case studies that emphasize how image and pattern (IAP) data are distributed and exchanged on sequential and parallel machines, and how the data communication patterns in low- and higher-level IAP computing differ from general numerical computation, what problems they cause and what opportunities they provide. The studies also describe how the images and matrices should be stored, accessed and distributed on different types of machines connected to the Internet, and how Internet resource sharing and data transmission change traditional IAP computing. Data Management and Internet Computing for Image/Pattern Analysis is divided into three parts: the first part describes several software approaches to IAP computing, citing several representative data communication patterns and related algorithms; the second part introduces hardware and Internet resource sharing in which a wide range of computer architectures are described and memory management issues are discussed; and the third part presents applications ranging from image coding, restoration and progressive transmission. Data Management and Internet Computing for Image/Pattern Analysis is an excellent reference for researchers and may be used as a text for advanced courses in image processing and pattern recognition.
Data Management and Query Processing in Semantic Web Databases
by Sven GroppeThe Semantic Web, which is intended to establish a machine-understandable Web, is currently changing from being an emerging trend to a technology used in complex real-world applications. A number of standards and techniques have been developed by the World Wide Web Consortium (W3C), e.g., the Resource Description Framework (RDF), which provides a general method for conceptual descriptions for Web resources, and SPARQL, an RDF querying language. Recent examples of large RDF data with billions of facts include the UniProt comprehensive catalog of protein sequence, function and annotation data, the RDF data extracted from Wikipedia, and Princeton University’s WordNet. Clearly, querying performance has become a key issue for Semantic Web applications.In his book, Groppe details various aspects of high-performance Semantic Web data management and query processing. His presentation fills the gap between Semantic Web and database books, which either fail to take into account the performance issues of large-scale data management or fail to exploit the special properties of Semantic Web data models and queries. After a general introduction to the relevant Semantic Web standards, he presents specialized indexing and sorting algorithms, adapted approaches for logical and physical query optimization, optimization possibilities when using the parallel database technologies of today’s multicore processors, and visual and embedded query languages.Groppe primarily targets researchers, students, and developers of large-scale Semantic Web applications. On the complementary book webpage readers will find additional material, such as an online demonstration of a query engine, and exercises, and their solutions, that challenge their comprehension of the topics presented.
Data Management. Data, Data Everywhere: 24th British National Conference on Databases, BNCOD 24, Glasgow, UK, July 3-5, 2007, Proceedings (Lecture Notes in Computer Science #4587)
by Richard Cooper Jessie KennedyThis book features the refereed proceedings from the 24th British National Conference on Databases, held in Glasgow, Scotland in July 2007. The eighteen full papers and seven poster papers are presented, together with two invited contributions. Papers are organized into topical sections covering data applications, searching XML documents, querying XML documents, XML transformation, clustering and security, data mining, and extraction.
Data Management for Mobile Computing (Advances in Database Systems #10)
by Evaggelia Pitoura George SamarasEarth date, August 11, 1997 "Beam me up Scottie!" "We cannot do it! This is not Star Trek's Enterprise. This is early years Earth." True, this is not yet the era of Star Trek, we cannot beam captain James T. Kirk or captain Jean Luc Pickard or an apple or anything else anywhere. What we can do though is beam information about Kirk or Pickard or an apple or an insurance agent. We can beam a record of a patient, the status of an engine, a weather report. We can beam this information anywhere, to mobile workers, to field engineers, to a track loading apples, to ships crossing the Oceans, to web surfers. We have reached a point where the promise of information access anywhere and anytime is close to realization. The enabling technology, wireless networks, exists; what remains to be achieved is providing the infrastructure and the software to support the promise. Universal access and management of information has been one of the driving forces in the evolution of computer technology. Central computing gave the ability to perform large and complex computations and advanced information manipulation. Advances in networking connected computers together and led to distributed computing. Web technology and the Internet went even further to provide hyper-linked information access and global computing. However, restricting access stations to physical location limits the boundary of the vision.
Data Management in a Connected World: Essays Dedicated to Hartmut Wedekind on the Occasion of His 70th Birthday (Lecture Notes in Computer Science #3551)
by Theo Härder Wolfgang Lehner Theo HärderData management systems play the most crucial role in building large application s- tems. Since modern applications are no longer single monolithic software blocks but highly flexible and configurable collections of cooperative services, the data mana- ment layer also has to adapt to these new requirements. Therefore, within recent years, data management systems have faced a tremendous shift from the central management of individual records in a transactional way to a platform for data integration, fede- tion, search services, and data analysis. This book addresses these new issues in the area of data management from multiple perspectives, in the form of individual contributions, and it outlines future challenges in the context of data management. These contributions are dedicated to Prof. em. Dr. Dr. -Ing. E. h. Hartmut Wedekind on the occasion of his 70th birthday, and were (co-)authored by some of his academic descendants. Prof. Wedekind is one of the most prominent figures of the database management community in Germany, and he enjoys an excellent international reputation as well. Over the last 35 years he greatly contributed to making relational database technology a success. As far back as the early 1970s, he covered—as the first author in Germany— the state of the art concerning the relational model and related issues in two widely used textbooks “Datenbanksysteme I” and “Datenbanksysteme II”. Without him, the idea of modeling complex-structured real-world scenarios in a relational way would be far less developed by now. Among Prof.
Data Management in Cloud, Grid and P2P Systems: 7th International Conference, Globe 2014, Munich, Germany, September 2-3, 2014. Proceedings (Lecture Notes in Computer Science #8648)
by Abdelkader Hameurlain Tran Khanh Dang Franck MorvanThis book constitutes the refereed proceedings of the 7th International Conference on Data Management in Grid and Peer-to-Peer Systems, Globe 2014, held in Munich, Germany, in September 2014, in conjunction with DEXA 2014. The 7 revised full papers presented were carefully reviewed and selected from 14 submissions. The papers are organized in the following topical sections: query processing in cloud, grid, and P2P systems: optimization and recommendation; MapReduce framework: data privacy and similarity search; data management in grid systems: protocol and recovery failure.