Show simple item record

dc.contributor.editorCurry, Edward
dc.contributor.editorAuer, Sören
dc.contributor.editorBerre, Arne J.
dc.contributor.editorMetzger, Andreas
dc.contributor.editorPerez, Maria S.
dc.contributor.editorZillner, Sonja
dc.date.accessioned2022-05-14T04:03:49Z
dc.date.available2022-05-14T04:03:49Z
dc.date.issued2022
dc.date.submitted2022-05-13T12:18:39Z
dc.identifierONIX_20220513_9783030783075_7
dc.identifierhttps://library.oapen.org/handle/20.500.12657/54415
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/81694
dc.description.abstractThis 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.
dc.languageEnglish
dc.rightsopen access
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data miningen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UN Databasesen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statisticsen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UB Information technology: general topicsen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systemsen_US
dc.subject.otherBig Data
dc.subject.otherData Management
dc.subject.otherData Processing
dc.subject.otherData Analytics
dc.subject.otherData Visualisation and User Interaction
dc.subject.otherKnowledge Discovery
dc.subject.otherInformation Retrieval
dc.titleTechnologies and Applications for Big Data Value
dc.typebook
oapen.identifier.doi10.1007/978-3-030-78307-5
oapen.relation.isPublishedBy9fa3421d-f917-4153-b9ab-fc337c396b5a
oapen.relation.isbn9783030783075
oapen.imprintSpringer International Publishing
oapen.pages544
oapen.place.publicationCham


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

open access
Except where otherwise noted, this item's license is described as open access