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https://doi.org/10.21256/zhaw-3177| Title: | Introduction to applied data science |
| Authors : | Stadelmann, Thilo Braschler, Martin Stockinger, Kurt |
| et. al : | No |
| Published in : | Applied data science : lessons learned for the data-driven business |
| Pages : | 3 |
| Pages to: | 16 |
| Editors of the parent work: | Braschler, Martin Stadelmann, Thilo Stockinger, Kurt |
| Publisher / Ed. Institution : | Springer |
| Publisher / Ed. Institution: | Cham |
| Issue Date: | 14-Jun-2019 |
| License (according to publishing contract) : | Licence according to publishing contract |
| Type of review: | Editorial review |
| Language : | English |
| Subjects : | Data science; Definition; Big data; Mega trend; Interdisciplinarity |
| Subject (DDC) : | 005: Computer programming, programs and data |
| Abstract: | What is data science? Attempts to define it can be made in one (prolonged) sentence, while it may take a whole book to demonstrate the meaning of this definition. This book introduces data science in an applied setting, by first giving a coherent overview of the background in Part I, and then presenting the nuts and bolts of the discipline by means of diverse use cases in Part II; finally, specific and insightful lessons learned are distilled in Part III. This chapter introduces the book and provides an answer to the following questions: What is data science? Where does it come from? What are its connections to big data and other mega trends? We claim that multidisciplinary roots and a focus on creating value lead to a discipline in the making that is inherently an interdisciplinary, applied science. |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Applied Information Technology (InIT) |
| Publication type: | Book part |
| DOI : | 10.21256/zhaw-3177 10.1007/978-3-030-11821-1_1 |
| ISBN: | 978-3-030-11821-1 978-3-030-11820-4 |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/17428 |
| Appears in Collections: | Publikationen School of Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ADS_2019_Introduction.pdf | preprint | 723.21 kB | Adobe PDF |  View/Open |
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