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Efficient Uploading of.Csv Datasets into a Non-Relational Database Management System

  • 2023
  • OriginalPaper
  • Chapter
Published in:
Authors
Matteo Fresta
Francesco Bellotti
Alessio Capello
Marianna Cossu
Luca Lazzaroni
Alessandro De Gloria
Riccardo Berta
Published in
Applications in Electronics Pervading Industry, Environment and Society
Publisher
Springer Nature Switzerland

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Abstract

The chapter addresses the growing need for efficient data processing in the era of IoT and Big Data, focusing on the integration of CSV datasets into non-relational databases. It introduces a solution that maps CSV data to a fixed schema-based database structure, using an additional configuration file to ensure accurate data insertion. The solution is demonstrated with real-world datasets from smart city and biomedical domains, showcasing its effectiveness, efficiency, and flexibility. The chapter concludes with potential future work, including a deeper analysis of CSV dataset compatibility and support for edge-cloud ML.
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previous chapter Enabling Predictive Maintenance on Electric Motors Through a Self-sustainable Wireless Sensor Node
next chapter Microcontroller Based Edge Computing for Pipe Leakage Detection
Title
Efficient Uploading of.Csv Datasets into a Non-Relational Database Management System
Authors
Matteo Fresta
Francesco Bellotti
Alessio Capello
Marianna Cossu
Luca Lazzaroni
Alessandro De Gloria
Riccardo Berta
Copyright Year
2023
Book
Applications in Electronics Pervading Industry, Environment and Society

Print ISBN: 978-3-031-30332-6

Electronic ISBN: 978-3-031-30333-3

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-3-031-30333-3_2
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