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Data-Centric Systems and Applications

SQL for Data Science

Data Cleaning, Wrangling and Analytics with Relational Databases

Authors: Badia, Antonio

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  • Explains SQL within the context of data science and introduces its different parts as they are needed for data analysis
  • Focuses on the steps that are very often given the short shift in traditional textbooks, like data loading, cleaning and pre-processing
  • Contains a lot of examples and exercises that can be played with using the open-source database systems MySQL and Postgres
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eBook $44.99
price for USA in USD
  • ISBN 978-3-030-57592-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $59.99
price for USA in USD
About this Textbook

This textbook explains SQL within the context of data science and introduces the different parts of SQL as they are needed for the tasks usually carried out during data analysis. Using the framework of the data life cycle, it focuses on the steps that are very often given the short shift in traditional textbooks, like data loading, cleaning and pre-processing.

The book is organized as follows. Chapter 1 describes the data life cycle, i.e. the sequence of stages from data acquisition to archiving, that data goes through as it is prepared and then actually analyzed, together with the different activities that take place at each stage. Chapter 2 gets into databases proper, explaining how relational databases organize data. Non-traditional data, like XML and text, are also covered. Chapter 3 introduces SQL queries, but unlike traditional textbooks, queries and their parts are described around typical data analysis tasks like data exploration, cleaning and transformation. Chapter 4 introduces some basic techniques for data analysis and shows how SQL can be used for some simple analyses without too much complication. Chapter 5 introduces additional SQL constructs that are important in a variety of situations and thus completes the coverage of SQL queries. Lastly, chapter 6 briefly explains how to use SQL from within R and from within Python programs. It focuses on how these languages can interact with a database, and how what has been learned about SQL can be leveraged to make life easier when using R or Python. All chapters contain a lot of examples and exercises on the way, and readers are encouraged to install the two open-source database systems (MySQL and Postgres) that are used throughout the book in order to practice and work on the exercises, because simply reading the book is much less useful than actually using it.

This book is for anyone interested in data science and/or databases. It just demands a bit of computer fluency, but no specific background on databases or data analysis. All concepts are introduced intuitively and with a minimum of specialized jargon. After going through this book, readers should be able to profitably learn more about data mining, machine learning, and database management from more advanced textbooks and courses.


About the authors

Antonio Badia is Associate Professor in the Department of Computer Science and Engineering at the University of Louisville, KY, USA. He has taught both introductory and advanced college database courses for more than 20 years, and created and taught a course on data management and analysis for non-computer science students. His research on database systems has been funded by NSF and others, and produced more than 50 publications in conferences and technical journals.



Table of contents (6 chapters)

Table of contents (6 chapters)

Buy this book

eBook $44.99
price for USA in USD
  • ISBN 978-3-030-57592-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $59.99
price for USA in USD
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Bibliographic Information

Bibliographic Information
Book Title
SQL for Data Science
Book Subtitle
Data Cleaning, Wrangling and Analytics with Relational Databases
Authors
Series Title
Data-Centric Systems and Applications
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-57592-2
DOI
10.1007/978-3-030-57592-2
Softcover ISBN
978-3-030-57591-5
Series ISSN
2197-9723
Edition Number
1
Number of Pages
XI, 285
Number of Illustrations
16 b/w illustrations
Topics