Go to main content

Technologies and applications for big data value / Edward Curry, Sören Auer, Arne J. Berre, Andreas Metzger, Maria S. Perez, Sonja Zillner, editors.

Curry, Edward, editor.; Auer, Sören, 1975- editor.; Berre, Arne J., editor.; Metzger, Andreas, editor.; Pérez, María S., editor.; Zillner, Sonja, editor.
2022
QA76.9.B45
Available Online
Formats
Format
BibTeX
MARCXML
TextMARC
MARC
DublinCore
EndNote
NLM
RefWorks
RIS
Add to Basket
Cite
Citation

Linked e-resources

Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Open access
Document Delivery Supplied
Open access

Details

Title
Technologies and applications for big data value / Edward Curry, Sören Auer, Arne J. Berre, Andreas Metzger, Maria S. Perez, Sonja Zillner, editors.
ISBN
9783030783075 (electronic bk.)
3030783073 (electronic bk.)
9783030783068
3030783065
DOI
https://doi.org/10.1007/978-3-030-78307-5
Published
Cham : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource : illustrations (chiefly color)
Item Number
10.1007/978-3-030-78307-5 doi
Call Number
QA76.9.B45
Dewey Decimal Classification
005.7
Summary
This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part "Technologies and Methods" contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part "Processes and Applications" details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.
Access Note
Open access
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed May 6, 2022).
Added Author
Curry, Edward, editor.
Auer, Sören, 1975- editor.
Berre, Arne J., editor.
Metzger, Andreas, editor.
Pérez, María S., editor.
Zillner, Sonja, editor.
Available in Other Form
Print version: 9783030783068
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
Technologies and Applications for Big Data Value
Part I: Technologies and Methods
Trade-Offs and Challenges of Serverless Data Analytics
Big Data and AI Pipeline Framework: Technology Analysis from a Benchmarking Perspective
An Elastic Software Architecture for Extreme-Scale Big Data Analytics
Privacy-Preserving Technologies for Trusted Data Spaces
Leveraging Data-Driven Infrastructure Management to Facilitate AIOps for Big Data Applications and Operations
Leveraging High-Performance Computing and Cloud Computing with Unified Big-DataWorkflows: The LEXIS Project
Part II: Processes and Applications
The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud Architectures
Applying AI to Manage Acute and Chronic Clinical Condition
3D Human Big Data Exchange Between the Healthcare and Garment Sectors
Using a Legal Knowledge Graph for Multilingual Compliance Services in Labor Law, Contract Management, and Geothermal Energy
Big Data Analytics in the Banking Sector: Guidelines and Lessons Learned from the CaixaBank Case
Data-Driven Artificial Intelligence and Predictive Analytics for the Maintenance of Industrial Machinery with Hybrid and Cognitive Digital Twins
Big Data Analytics in the Manufacturing Sector: Guidelines and Lessons Learned Through the Centro Ricerche FIAT (CRF) Case
Next-Generation Big Data-Driven Factory 4.0 Operations and Optimization: The Boost 4.0 Experience
Big Data-Driven Industry 4.0 Service Engineering Large-Scale Trials: The Boost 4.0 Experience
Model-Based Engineering and Semantic Interoperability for Trusted Digital Twins Big Data Connection Across the Product Lifecycle
A Data Science Pipeline for Big Linked Earth Observation Data
Towards Cognitive Ports of the Futures
Distributed Big Data Analytics in a Smart City
Processing Big Data in Motion: Core Components and System Architectures with Applications to the Maritime Domain
Knowledge Modeling and Incident Analysis for Special Cargo.

Browse Subjects

Show more subjects...

Statistics

from
to
Export