Technologies and Applications for Big Data Value

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 b...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Curry, Edward (Editor), Auer, Sören (Editor), Berre, Arne J. (Editor), Metzger, Andreas (Editor), Perez, Maria S. (Editor), Zillner, Sonja (Editor)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2022.
Edition:1st ed. 2022.
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Online Access:Link to Metadata
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Table of Contents:
  • 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 SciencePipeline 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.