Overview
- Covers all of data warehousing & analytics, incl. transformation, preparation, integration, aggregation, and analysis
- Explains concepts in a very practical way based on numerous case studies and exercises
- Datasets, sample codes, solutions to exercises and teaching slides are available on a dedicated web page
Part of the book series: Data-Centric Systems and Applications (DCSA)
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Table of contents (21 chapters)
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Front Matter
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Star Schema
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Front Matter
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Snowflake and Bridge Tables
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Front Matter
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Advanced Dimension
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Front Matter
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Multi-Fact and Multi-Input
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Front Matter
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Data Warehousing Granularity and Evolution
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Front Matter
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Keywords
About this book
This textbook covers all central activities of data warehousing and analytics, including transformation, preparation, aggregation, integration, and analysis. It discusses the full spectrum of the journey of data from operational/transactional databases, to data warehouses and data analytics; as well as the role that data warehousing plays in the data processing lifecycle. It also explains in detail how data warehouses may be used by data engines, such as BI tools and analytics algorithms to produce reports, dashboards, patterns, and other useful information and knowledge.
The book is divided into six parts, ranging from the basics of data warehouse design (Part I - Star Schema, Part II - Snowflake and Bridge Tables, Part III - Advanced Dimensions, and Part IV - Multi-Fact and Multi-Input), to more advanced data warehousing concepts (Part V - Data Warehousing and Evolution) and data analytics (Part VI - OLAP, BI, and Analytics).
This textbook approaches data warehousing from the case study angle. Each chapter presents one or more case studies to thoroughly explain the concepts and has different levels of difficulty, hence learning is incremental. In addition, every chapter has also a section on further readings which give pointers and references to research papers related to the chapter. All these features make the book ideally suited for either introductory courses on data warehousing and data analytics, or even for self-studies by professionals. The book is accompanied by a web page that includes all the used datasets and codes as well as slides and solutions to exercises.
Authors and Affiliations
About the authors
Wenny Rahayu is a Professor in Computer Science and currently the Dean of the School of Engineering and Mathematical Sciences, La Trobe University, Australia. She graduated with a PhD degree in Computer Science, specializing in Databases from La Trobe University in 2001. Her PhD thesis has been awarded the Best PhD Thesis Award by The Computing Research and Education Association of Australasia (CORE), an association of university departments of computer science in Australia and New Zealand. She has published more than 300 papers and successfully supervised 17 PhD students in databases.
Bibliographic Information
Book Title: Data Warehousing and Analytics
Book Subtitle: Fueling the Data Engine
Authors: David Taniar, Wenny Rahayu
Series Title: Data-Centric Systems and Applications
DOI: https://doi.org/10.1007/978-3-030-81979-8
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-81978-1Published: 05 February 2022
eBook ISBN: 978-3-030-81979-8Published: 04 February 2022
Series ISSN: 2197-9723
Series E-ISSN: 2197-974X
Edition Number: 1
Number of Pages: XVIII, 635
Number of Illustrations: 119 b/w illustrations, 262 illustrations in colour
Topics: Database Management, Big Data, Statistics, general, Information Storage and Retrieval