Author: Xianwu Zeng
Publisher: Springer Nature
ISBN: 9819976030
Category : Technology & Engineering
Languages : en
Pages : 426
Book Description
This book focuses on the key technology applied Internet of things and smart grid, which include some novel ICT technologies such as big data, edge computing, 5G, and wide area wireless communication technology. The mutual penetration, deep integration, and wide application of smart grid and IoT effectively integrate communication infrastructure resources and power system infrastructure resources, further realize energy conservation and emission reduction, improve the level of grid informatization, automation, and interaction, and improve grid operation capacity and quality of service. These key technologies are presented and studied in detail, which help readers deeply understand those key technologies to apply IoT and grid. The book benefits researchers, engineers, and graduate students in the fields of IoT and energy systems, etc.
Key Technologies of Internet of Things and Smart Grid
Author: Xianwu Zeng
Publisher: Springer Nature
ISBN: 9819976030
Category : Technology & Engineering
Languages : en
Pages : 426
Book Description
This book focuses on the key technology applied Internet of things and smart grid, which include some novel ICT technologies such as big data, edge computing, 5G, and wide area wireless communication technology. The mutual penetration, deep integration, and wide application of smart grid and IoT effectively integrate communication infrastructure resources and power system infrastructure resources, further realize energy conservation and emission reduction, improve the level of grid informatization, automation, and interaction, and improve grid operation capacity and quality of service. These key technologies are presented and studied in detail, which help readers deeply understand those key technologies to apply IoT and grid. The book benefits researchers, engineers, and graduate students in the fields of IoT and energy systems, etc.
Publisher: Springer Nature
ISBN: 9819976030
Category : Technology & Engineering
Languages : en
Pages : 426
Book Description
This book focuses on the key technology applied Internet of things and smart grid, which include some novel ICT technologies such as big data, edge computing, 5G, and wide area wireless communication technology. The mutual penetration, deep integration, and wide application of smart grid and IoT effectively integrate communication infrastructure resources and power system infrastructure resources, further realize energy conservation and emission reduction, improve the level of grid informatization, automation, and interaction, and improve grid operation capacity and quality of service. These key technologies are presented and studied in detail, which help readers deeply understand those key technologies to apply IoT and grid. The book benefits researchers, engineers, and graduate students in the fields of IoT and energy systems, etc.
Sensing, Data Managing, and Control Technologies for Agricultural Systems
Author: Shaochun Ma
Publisher: Springer Nature
ISBN: 3031038347
Category : Technology & Engineering
Languages : en
Pages : 336
Book Description
Agricultural automation is the emerging technologies which heavily rely on computer-integrated management and advanced control systems. The tedious farming tasks had been taken over by agricultural machines in last century, in new millennium, computer-aided systems, automation, and robotics has been applied to precisely manage agricultural production system. With agricultural automation technologies, sustainable agriculture is being developed based on efficient use of land, increased conservation of water, fertilizer and energy resources. The agricultural automation technologies refer to related areas in sensing & perception, reasoning & learning, data communication, and task planning & execution. Since the literature on this diverse subject is widely scattered, it is necessary to review current status and capture the future challenges through a comprehensive monograph. In this book we focus on agricultural automation and provide critical reviews of advanced control technologies, their merits and limitations, application areas and research opportunities for further development. This collection thus serves as an authoritative treatise that can help researchers, engineers, educators, and students in the field of sensing, control, and automation technologies for production agriculture.
Publisher: Springer Nature
ISBN: 3031038347
Category : Technology & Engineering
Languages : en
Pages : 336
Book Description
Agricultural automation is the emerging technologies which heavily rely on computer-integrated management and advanced control systems. The tedious farming tasks had been taken over by agricultural machines in last century, in new millennium, computer-aided systems, automation, and robotics has been applied to precisely manage agricultural production system. With agricultural automation technologies, sustainable agriculture is being developed based on efficient use of land, increased conservation of water, fertilizer and energy resources. The agricultural automation technologies refer to related areas in sensing & perception, reasoning & learning, data communication, and task planning & execution. Since the literature on this diverse subject is widely scattered, it is necessary to review current status and capture the future challenges through a comprehensive monograph. In this book we focus on agricultural automation and provide critical reviews of advanced control technologies, their merits and limitations, application areas and research opportunities for further development. This collection thus serves as an authoritative treatise that can help researchers, engineers, educators, and students in the field of sensing, control, and automation technologies for production agriculture.
Data Management, Analytics and Innovation
Author: Neha Sharma
Publisher: Springer Nature
ISBN: 9813299495
Category : Technology & Engineering
Languages : en
Pages : 727
Book Description
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.
Publisher: Springer Nature
ISBN: 9813299495
Category : Technology & Engineering
Languages : en
Pages : 727
Book Description
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.
Advanced Data Management
Author: Lena Wiese
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110433079
Category : Computers
Languages : en
Pages : 468
Book Description
Advanced data management has always been at the core of efficient database and information systems. Recent trends like big data and cloud computing have aggravated the need for sophisticated and flexible data storage and processing solutions. This book provides a comprehensive coverage of the principles of data management developed in the last decades with a focus on data structures and query languages. It treats a wealth of different data models and surveys the foundations of structuring, processing, storing and querying data according these models. Starting off with the topic of database design, it further discusses weaknesses of the relational data model, and then proceeds to convey the basics of graph data, tree-structured XML data, key-value pairs and nested, semi-structured JSON data, columnar and record-oriented data as well as object-oriented data. The final chapters round the book off with an analysis of fragmentation, replication and consistency strategies for data management in distributed databases as well as recommendations for handling polyglot persistence in multi-model databases and multi-database architectures. While primarily geared towards students of Master-level courses in Computer Science and related areas, this book may also be of benefit to practitioners looking for a reference book on data modeling and query processing. It provides both theoretical depth and a concise treatment of open source technologies currently on the market.
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110433079
Category : Computers
Languages : en
Pages : 468
Book Description
Advanced data management has always been at the core of efficient database and information systems. Recent trends like big data and cloud computing have aggravated the need for sophisticated and flexible data storage and processing solutions. This book provides a comprehensive coverage of the principles of data management developed in the last decades with a focus on data structures and query languages. It treats a wealth of different data models and surveys the foundations of structuring, processing, storing and querying data according these models. Starting off with the topic of database design, it further discusses weaknesses of the relational data model, and then proceeds to convey the basics of graph data, tree-structured XML data, key-value pairs and nested, semi-structured JSON data, columnar and record-oriented data as well as object-oriented data. The final chapters round the book off with an analysis of fragmentation, replication and consistency strategies for data management in distributed databases as well as recommendations for handling polyglot persistence in multi-model databases and multi-database architectures. While primarily geared towards students of Master-level courses in Computer Science and related areas, this book may also be of benefit to practitioners looking for a reference book on data modeling and query processing. It provides both theoretical depth and a concise treatment of open source technologies currently on the market.
Managing Data in Motion
Author: April Reeve
Publisher: Newnes
ISBN: 0123977916
Category : Computers
Languages : en
Pages : 203
Book Description
Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired. The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects. - Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types - Explains, in non-technical terms, the architecture and components required to perform data integration - Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"
Publisher: Newnes
ISBN: 0123977916
Category : Computers
Languages : en
Pages : 203
Book Description
Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired. The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects. - Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types - Explains, in non-technical terms, the architecture and components required to perform data integration - Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"
Big Scientific Data Management
Author: Jianhui Li
Publisher: Springer
ISBN: 3030280616
Category : Computers
Languages : en
Pages : 346
Book Description
This book constitutes the refereed proceedings of the First International Conference on Big Scientific Data Management, BigSDM 2018, held in Beijing, Greece, in November/December 2018. The 24 full papers presented together with 7 short papers were carefully reviewed and selected from 86 submissions. The topics involved application cases in the big scientific data management, paradigms for enhancing scientific discovery through big data, data management challenges posed by big scientific data, machine learning methods to facilitate scientific discovery, science platforms and storage systems for large scale scientific applications, data cleansing and quality assurance of science data, and data policies.
Publisher: Springer
ISBN: 3030280616
Category : Computers
Languages : en
Pages : 346
Book Description
This book constitutes the refereed proceedings of the First International Conference on Big Scientific Data Management, BigSDM 2018, held in Beijing, Greece, in November/December 2018. The 24 full papers presented together with 7 short papers were carefully reviewed and selected from 86 submissions. The topics involved application cases in the big scientific data management, paradigms for enhancing scientific discovery through big data, data management challenges posed by big scientific data, machine learning methods to facilitate scientific discovery, science platforms and storage systems for large scale scientific applications, data cleansing and quality assurance of science data, and data policies.
DAMA-DMBOK
Author: Dama International
Publisher:
ISBN: 9781634622349
Category : Database management
Languages : en
Pages : 628
Book Description
Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.
Publisher:
ISBN: 9781634622349
Category : Database management
Languages : en
Pages : 628
Book Description
Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.
Data Management Systems
Author: Bhavani Thuraisingham
Publisher: CRC Press
ISBN: 9780849394935
Category : Computers
Languages : en
Pages : 276
Book Description
As the information contained in databases has become a critical resource in organizations, efficient access to that information and the ability to share it among different users and across different systems has become an urgent need. The interoperability of heterogeneous database systems-literally, the ability to access information between or among differing types of databases, is the topic of this timely book. In the last two decades, tremendous improvements in tools and technologies have resulted in new products that provide distributed data processing capabilities. This book describes these tools and emerging technologies, explaining the essential concepts behind the topics but focusing on practical applications. Selected products are discussed to illustrate the characteristics of the different technologies. This is an ideal source for anyone who needs a broad perspective on heterogeneous database integration and related technologies.
Publisher: CRC Press
ISBN: 9780849394935
Category : Computers
Languages : en
Pages : 276
Book Description
As the information contained in databases has become a critical resource in organizations, efficient access to that information and the ability to share it among different users and across different systems has become an urgent need. The interoperability of heterogeneous database systems-literally, the ability to access information between or among differing types of databases, is the topic of this timely book. In the last two decades, tremendous improvements in tools and technologies have resulted in new products that provide distributed data processing capabilities. This book describes these tools and emerging technologies, explaining the essential concepts behind the topics but focusing on practical applications. Selected products are discussed to illustrate the characteristics of the different technologies. This is an ideal source for anyone who needs a broad perspective on heterogeneous database integration and related technologies.
Principles of Database Management
Author: Wilfried Lemahieu
Publisher: Cambridge University Press
ISBN: 1107186129
Category : Computers
Languages : en
Pages : 817
Book Description
Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.
Publisher: Cambridge University Press
ISBN: 1107186129
Category : Computers
Languages : en
Pages : 817
Book Description
Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.
Enterprise Master Data Management
Author: Allen Dreibelbis
Publisher: Pearson Education
ISBN: 0132704277
Category : Business & Economics
Languages : en
Pages : 833
Book Description
The Only Complete Technical Primer for MDM Planners, Architects, and Implementers Companies moving toward flexible SOA architectures often face difficult information management and integration challenges. The master data they rely on is often stored and managed in ways that are redundant, inconsistent, inaccessible, non-standardized, and poorly governed. Using Master Data Management (MDM), organizations can regain control of their master data, improve corresponding business processes, and maximize its value in SOA environments. Enterprise Master Data Management provides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical analysts, consultants, solution designers, and senior IT decisionmakers. Written by the IBM ® data management innovators who are pioneering MDM, this book systematically introduces MDM’s key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA. Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere else—everything you need to establish a consistent, manageable set of master data, and use it for competitive advantage. Coverage includes How MDM and SOA complement each other Using the MDM Reference Architecture to position and design MDM solutions within an enterprise Assessing the value and risks to master data and applying the right security controls Using PIM-MDM and CDI-MDM Solution Blueprints to address industry-specific information management challenges Explaining MDM patterns as enablers to accelerate consistent MDM deployments Incorporating MDM solutions into existing IT landscapes via MDM Integration Blueprints Leveraging master data as an enterprise asset—bringing people, processes, and technology together with MDM and data governance Best practices in MDM deployment, including data warehouse and SAP integration
Publisher: Pearson Education
ISBN: 0132704277
Category : Business & Economics
Languages : en
Pages : 833
Book Description
The Only Complete Technical Primer for MDM Planners, Architects, and Implementers Companies moving toward flexible SOA architectures often face difficult information management and integration challenges. The master data they rely on is often stored and managed in ways that are redundant, inconsistent, inaccessible, non-standardized, and poorly governed. Using Master Data Management (MDM), organizations can regain control of their master data, improve corresponding business processes, and maximize its value in SOA environments. Enterprise Master Data Management provides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical analysts, consultants, solution designers, and senior IT decisionmakers. Written by the IBM ® data management innovators who are pioneering MDM, this book systematically introduces MDM’s key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA. Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere else—everything you need to establish a consistent, manageable set of master data, and use it for competitive advantage. Coverage includes How MDM and SOA complement each other Using the MDM Reference Architecture to position and design MDM solutions within an enterprise Assessing the value and risks to master data and applying the right security controls Using PIM-MDM and CDI-MDM Solution Blueprints to address industry-specific information management challenges Explaining MDM patterns as enablers to accelerate consistent MDM deployments Incorporating MDM solutions into existing IT landscapes via MDM Integration Blueprints Leveraging master data as an enterprise asset—bringing people, processes, and technology together with MDM and data governance Best practices in MDM deployment, including data warehouse and SAP integration