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Getting Started with Engineering Data Science

Engineering data science is an emerging interdisciplinary field that leverages data-driven techniques and engineering principles to solve complex problems, optimise processes, and foster innovation. This paper provides a broad entry point to data science for engineering practitioners and demonstrates how data science is augmenting the understanding and modelling of complex systems.

This paper emphasises the important role that data science is now playing in engineering fields before going onto describe the data science process and discuss the distinctive qualities of engineering data. Examples of value propositions and applications of data science across the lifecycle are provided. To conclude, guidance is provided on how to get started with engineering data science and machine learning.


C​ontents

SectionTitlePage
1Introduction1
1.1Definitions2
1.2The Role of Data Science4
2The Process of Data Science6
2.1Business Understanding7
2.2Data Understanding8
2.3Data Preparation8
2.4Modelling9
2.5Evaluation9
2.6Deployment10
3Engineering Data - Attributes & Methods12
3.1Size of Data Sets12
3.2Quality12
3.3Outliers12
3.4Geometric Format13
3.5Multi-Dimensionality13
3.6Skewness13
3.7Sparsity of Crucial Events and Imbalanced Datasets13
3.8The Importance of Context14
4The Value of Engineering Data Science15
4.1Design15
4.2Manufacturing16
4.3Operational17
5Recommendations19
5.1Resources21
6Acronyms and Abbreviations23
7References24

International Standard Book Number: 978-1-83979-229-8
First Published: 2024
Order Reference:
Published By:
NAFEMS
Springwood - Booths Park
Chelford Road
Knutsford
WA16 8QZ
United Kingdom
Copyright © NAFEMS 2024. All rights reserved. No part of this publication may be reproduced or distributed in any form or by any means, or stored in a data base or retrieval system without prior permission of the publisher.

Document Details

ReferenceHT56
AuthorsAmode. C Buchholz. C DePauw. T Pinon Fischer. O Karl. A Mooney. S
LanguageEnglish
AudiencesAnalyst Manager
TypePublication
Date 3rd September 2024
OrganisationNAFEMS
RegionGlobal

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