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Development Methodologies for Big Data Analytics Systems

Overview of attention for book
Development Methodologies for Big Data Analytics Systems
Springer International Publishing

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Open Source IT for Delivering Big Data Analytics Systems as Services: A Selective Review
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    Chapter 2 The Role of Machine Learning in Big Data Analytics: Current Practices and Challenges
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    Chapter 3 The Data Value Chain Ontology
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    Chapter 4 Requirements for Machine Learning Methodology Software Tooling
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    Chapter 5 A Selective Conceptual Review of CRISP-DM and DDSL Development Methodologies for Big Data Analytics Systems
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    Chapter 6 A Selective Comparative Review of CRISP-DM and TDSP Development Methodologies for Big Data Analytics Systems
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    Chapter 7 BDAS-EPM: An Integrated Evolution Process Model for Big Data Analytics Systems
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    Chapter 8 Big Data Adoption Factors and Development Methodologies: A Multiple Case Study Analysis
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    Chapter 9 Detection of Breast Cancer in Mammography Using Pretrained Convolutional Neural Networks with Fine-Tuning
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    Chapter 10 Challenges and Opportunities of Intercompany Big Data Analytics in Supply Chains
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    Chapter 11 From Big Data to Big Insights: A Synthesis of Real-World Applications of Big Data Analytics
Attention for Chapter 10: Challenges and Opportunities of Intercompany Big Data Analytics in Supply Chains
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Chapter title
Challenges and Opportunities of Intercompany Big Data Analytics in Supply Chains
Chapter number 10
Book title
Development Methodologies for Big Data Analytics Systems
Published in
Transactions on Computational Science and Computational Intelligence, January 2024
DOI 10.1007/978-3-031-40956-1_10
Book ISBNs
978-3-03-140955-4, 978-3-03-140956-1
Authors

Kallisch, J., Marx-Gómez, Jorge, Wunck, C.

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