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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 Chakrabarti

The 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 It includes original and previously unpublished international research work highlighting research domains from different perspectives.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 2022 (Lecture Notes on Data Engineering and Communications Technologies #137)

by Alfred M. Bruckstein C. Mohan Saptarsi Goswami Inderjit Singh Barara Amol Goje

This 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 Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and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 2018, Volume 2 (Advances In Intelligent Systems and Computing #839)

by Amlan Chakrabarti Neha Sharma Valentina Emilia Balas

The 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 Original, unpublished research work highlighting specific research domains from all viewpoints are contributed from scientists throughout the globe.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 2024, Volume 2 (Lecture Notes in Networks and Systems #998)

by Amlan Chakrabarti Neha Sharma Alfred M. Bruckstein Amol C. Goje

This 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 8th International Conference on Data Management, Analytics and Innovation (ICDMAI 2024), held during 19–21 January 2024 in Vellore Institute of Technology, Vellore, 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. The book is divided into two volumes.

Data Management, Analytics and Innovation: Proceedings of ICDMAI 2024, Volume 1 (Lecture Notes in Networks and Systems #997)

by Amlan Chakrabarti Neha Sharma Alfred M. Bruckstein Amol C. Goje

This 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 8th International Conference on Data Management, Analytics and Innovation (ICDMAI 2024), held during 19–21 January 2024 in Vellore Institute of Technology, Vellore, 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. The book is divided into two volumes.

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 Balas

This 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. Bruckstein

This 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. Bruckstein

This 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 Martinovic

This 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 Martinovic

This 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. Bruckstein

This 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 Far

Data 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 Luo

This 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 Gang Luo Lixia Yao

This 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 Query Processing in Semantic Web Databases

by Sven Groppe

The 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 at Scale: Best Practices For Enterprise Architecture

by Piethein Strengholt

As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption.Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed.Examine data management trends, including technological developments, regulatory requirements, and privacy concernsGo deep into the Scaled Architecture and learn how the pieces fit togetherExplore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata

Data Management Essentials Using SAS and JMP

by Kezik, Julie , MS and Hill, Melissa , MPH Julie Kezik Melissa Mph Hill

SAS programming is a creative and iterative process designed to empower you to make the most of your organization's data. This friendly guide provides you with a repertoire of essential SAS tools for data management, whether you are a new or an infrequent user. Most useful to students and programmers with little or no SAS experience, it takes a no-frills, hands-on tutorial approach to getting started with the software. You will find immediate guidance in navigating, exploring, visualizing, cleaning, formatting, and reporting on data using SAS and JMP. Step-by-step demonstrations, screenshots, handy tips, and practical exercises with solutions equip you to explore, interpret, process and summarize data independently, efficiently and effectively.

Data Management of Protein Interaction Networks

by Mario Cannataro Pietro Hiram Guzzi

Current PPI databases do not offer sophisticated querying interfaces and especially do not integrate existing information about proteins. Current algorithms for PIN analysis use only topological information, while emerging approaches attempt to exploit the biological knowledge related to proteins and kinds of interaction, e. g. protein function, localization, structure, described in Gene Ontology or PDB. The book discusses technologies, standards and databases for, respectively, generating, representing and storing PPI data. It also describes main algorithms and tools for the analysis, comparison and knowledge extraction from PINs. Moreover, some case studies and applications of PINs are also discussed.

Data Management on New Hardware: 7th International Workshop on Accelerating Data Analysis and Data Management Systems Using Modern Processor and Storage Architectures, ADMS 2016 and 4th International Workshop on In-Memory Data Management and Analytics, IMDM 2016, New Delhi, India, September 1, 2016, Revised Selected Papers (Lecture Notes in Computer Science #10195)

by Justin Levandoski Andrew Pavlo Spyros Blanas Rajesh Bordawekar Tirthankar Lahiri

This book contains selected papers from the 7th International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures, ADMS 2016, and the 4th International Workshop on In-Memory Data Management and Analytics, IMDM 2016, held in New Dehli, India, in September 2016. The joint Workshops were co-located with VLDB 2016. The 9 papers presented were carefully reviewed and selected from 18 submissions. They investigate opportunities in accelerating analytics/data management systems and workloads (including traditional OLTP, data warehousing/OLAP, ETL streaming/real-time, business analytics, and XML/RDF processing) running memory-only environments, using processors (e. g. commodity and specialized multi-core, GPUs and FPGAs, storage systems (e. g. storage-class memories like SSDs and phase-change memory), and hybrid programming models like CUDA, OpenCL, and Open ACC. The papers also explore the interplay between overall system design, core algorithms, query optimization strategies, programming approaches, performance modeling and evaluation, from the perspective of data management applications.

Data Management Technologies and Applications: 10th International Conference, DATA 2021, Virtual Event, July 6–8, 2021, and 11th International Conference, DATA 2022, Lisbon, Portugal, July 11-13, 2022, Revised Selected Papers (Communications in Computer and Information Science #1860)

by Alfredo Cuzzocrea Oleg Gusikhin Slimane Hammoudi Christoph Quix

This book constitutes the refereed post-proceedings of the 10th International Conference and 11th International Conference on Data Management Technologies and Applications, DATA 2021 and DATA 2022, was held virtually due to the COVID-19 crisis on July 6–8, 2021 and in Lisbon, Portugal on July 11-13, 2022.The 11 full papers included in this book were carefully reviewed and selected from 148 submissions. They were organized in topical sections as follows: engineers and practitioners interested on databases, big data, data mining, data management, data security and other aspects of information systems and technology involving advanced applications of data.

Data Management Technologies and Applications: 12th International Conference, DATA 2023, Rome, Italy, July 11–13, 2023, Revised Selected Papers (Communications in Computer and Information Science #2105)

by Alfredo Cuzzocrea Slimane Hammoudi Oleg Gusikhin

This book constitutes the proceedings of the 12th International Conference on Data Management Technologies and Applications, DATA 2023 , held in Rome,Italy during July 11–13, 2023, Proceedings. The 6 full paper were carefully reviewed and selected from 106 submissions. The papers are organized in subject areas as follows: Big Data Applications, Data Analytics, Data Science, NoSQL Databases, Social Data Analytics, Dimensional Modelling, Deep Learning and Big Data, Decision Support Systems, Data Warehouse Management and Data Management for Analytics.

Data Management Technologies and Applications: 6th International Conference, DATA 2017, Madrid, Spain, July 24–26, 2017, Revised Selected Papers (Communications in Computer and Information Science #814)

by Joaquim Filipe Jorge Bernardino Christoph Quix

This book constitutes the thoroughly refereed proceedings of the 6th International Conference on Data Management Technologies and Applications, DATA 2017, held in Madrid, Spain, in July 2017. The 13 revised full papers were carefully reviewed and selected from 66 submissions. The papers deal with the following topics: databases, big data, data mining, data management, data security, and other aspects of information systems and technology involving advanced applications of data.

Data Management Technologies and Applications: 8th International Conference, DATA 2019, Prague, Czech Republic, July 26–28, 2019, Revised Selected Papers (Communications in Computer and Information Science #1255)

by Slimane Hammoudi Christoph Quix Jorge Bernardino

This book constitutes the thoroughly refereed proceedings of the 8th International Conference on Data Management Technologies and Applications, DATA 2019, held in Prague, Czech Republic, in July 2019. The 8 revised full papers were carefully reviewed and selected from 90 submissions. The papers deal with the following topics: decision support systems, data analytics, data and information quality, digital rights management, big data, knowledge management, ontology engineering, digital libraries, mobile databases, object-oriented database systems, and data integrity.

Data Management Technologies and Applications: 9th International Conference, DATA 2020, Virtual Event, July 7–9, 2020, Revised Selected Papers (Communications in Computer and Information Science #1446)

by Slimane Hammoudi Christoph Quix Jorge Bernardino

This book constitutes the thoroughly refereed proceedings of the 9th International Conference on Data Management Technologies and Applications, DATA 2020, which was supposed to take place in Paris, France, in July 2020. Due to the Covid-19 pandemic the event was held virtually. The 14 revised full papers were carefully reviewed and selected from 70 submissions. The papers deal with the following topics: datamining; decision support systems; data analytics; data and information quality; digital rights management; big data; knowledge management; ontology engineering; digital libraries; mobile databases; object-oriented database systems; data integrity.

Data Management Technologies and Applications: 5th International Conference, DATA 2016, Colmar, France, July 24-26, 2016, Revised Selected Papers (Communications in Computer and Information Science #737)

by Markus Helfert Chiara Francalanci

This book constitutes the thoroughly refereed proceedings of the Third International Conference on Data Technologies and Applications, DATA 2014, held in Vienna, Austria, in August 2014. The 12 revised full papers were carefully reviewed and selected from 87 submissions. The papers deal with the following topics: databases, data warehousing, data mining, data management, data security, knowledge and information systems and technologies; advanced application of data.

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