Preface; Part I. Databases and Database Design: 1. Fundamental concepts of database management; 2. Architecture and categorization of DBMSs; 3. Conceptual data modeling using the (E)ER model and UML class diagram; 4. Organizational aspects of data management; Part II. Types of Database Systems: 5. Legacy databases; 6. Relational databases: the relational model; 7. Relational databases: structured query language (SQL); 8. Object oriented databases and object persistence; 9. Extended relational databases; 10. XML databases; 11. NoSQL databases; Part III. Physical Data Storage, Transaction Management, and Database Access: 12. Physical file organization and indexing; 13. Physical database organization; 14. Basics of transaction management; 15. Accessing databases and database APIs; 16. Data distribution and distributed transaction management; Part IV. Data Warehousing, Data Governance and (Big) Data Analytics: 17. Data warehousing and business intelligence; 18. Data integration, data quality and data governance; 19. Big data; 20. Analytics; Appendix A. Cases and questions; Appendix B. Using the online environment; Appendix C. Answer key to select review questions; Glossary; Index.
Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.
Wilfried Lemahieu is a professor at KU Leuven, Belgium, Faculty of Economics and Business, where he also holds the position of Dean. His teaching, for which he was awarded a 'best teacher recognition' includes courses on database management, enterprise information management and management informatics. His research focuses on big data storage and integration, data quality, business process management and service-oriented architectures. In this context, he collaborates extensively with a variety of industry partners, both local and international. His research is published in renowned international journals and he is a frequent lecturer for both academic and industry audiences. Seppe vanden Broucke works as an assistant professor at the Faculty of Economics and Business, KU Leuven, Belgium. His research interests include business data mining and analytics, machine learning, process management and process mining. His work has been published in well-known international journals and presented at top conferences. He is also author of the book Beginning Java Programming (2015) of which more than 4000 copies were sold and which was also translated in Russian. Seppe's teaching includes advanced analytics, big data and information management courses. He also frequently teaches for industry and business audiences. Bart Baesens is a professor of Big Data and Analytics at KU Leuven, Belgium and a lecturer at the University of Southampton. He has done extensive research on big data and analytics, credit risk modeling, fraud detection and marketing analytics. He has written more than 200 scientific papers some of which have been published in well-known international journals (e.g. MIS Quarterly, Machine Learning, Management Science, MIT Sloan Management Review and IEEE Transactions on Knowledge and Data Engineering) and presented at international top conferences (e.g. ICIS, KDD, CAISE). He received various best paper and best speaker awards. Bart is the author of 6 books: Credit Risk Management: Basic Concepts (2009), Analytics in a Big Data World (2014), Beginning Java Programming (2015), Fraud Analytics using Descriptive, Predictive and Social Network Techniques (2015), Credit Risk Analytics (2016) and Profit-Driven Business Analytics (2017). He sold more than 15.000 copies of these books worldwide, some of which have been translated in Chinese, Russian and Korean.
'Although there have been a series of classical textbooks on
database systems, the new dramatic advances call for an updated
text covering the latest significant topics, such as big data
analytics, No-SQL and much more. Fortunately, this is exactly what
this book has to offer. It is highly desirable for training the
next generation of data management professionals.' Jian Pei, Simon
Fraser University, Canada
'I haven't seen an as up-to-date and comprehensive textbook for
Database Management as this one in many years. Principles of
Database Management combines a number of classical and recent
topics concerning Data Modeling, Relational Databases,
Object-Oriented Databases, XML, Distributed Data Management, NoSQL
and Big Data in an unprecedented manner. The authors did a great
job in stitching these topics into one coherent and compelling
story that will serve as an ideal basis for teaching both
introductory and advanced courses.' Martin Theobald, University of
Luxembourg
'This is a very timely book with outstanding coverage of database
topics and excellent treatment of database details. It not only
gives very solid discussions of traditional topics like data
modeling and relational databases but also contains refreshing
contents on frontier topics such as XML databases, NoSQL databases,
big data, and analytics. For those reasons, this will be a good
book for database professionals who will keep using it for all
stages of database studies and works.' J. Leon Zhao, City
University of Hong Kong
'This accessible, authoritative book introduces the reader the most
important fundamental concepts of data management, while providing
a practical view of recent advances. Both are essential for data
professionals today.' Foster Provost, New York University, Stern
School of Business
'This guide to big and small data management addresses both
fundamental principles and practical deployment. It reviews a range
of databases and their relevance for analytics. The book is useful
to practitioners because it contains many case studies, links to
open-source software, and a very useful abstraction of analytics
that will help them better choose solutions. It is important to
academics because it promotes database principles which are key to
successful and sustainable data science.' Sihem Amer-Yahia,
Laboratoire d'Informatique de Grenoble and Editor-in-Chief the
International Journal on Very Large DataBases
'This book covers everything you will need to teach in a database
implementation and design class. With some chapters covering big
data, analytic models/methods, and No-SQL, it can keep our students
up-to-date with these new technologies in data management related
topics.' Han-fen Hu, University of Nevada, Las Vegas
'As we are entering a new technological era of intelligent machines
powered by data-driven algorithms, understanding fundamental
concepts of data management and their most current practical
applications has become more important than ever. This book is a
timely guide for anyone interested in getting up to speed with the
state of the art in database systems, big data technologies, and
data science. It is full of insightful examples and case studies
with direct industrial relevance.' Nesime Tatbul, Intel Labs and
Massachusetts Institute of Technology
'It is a pleasure to study this new book on database systems. The
book offers a fantastically fresh approach to database teaching.
The mix of theoretical and practical contents is almost perfect,
the content is up-to-date and covers the recent ones, the examples
are nice, and the database testbed provides an excellent way of
understanding the concepts. Coupled with the authors 'expertise,
this book is an important addition to the database field.' Arnab
Bhattacharya, Indian Institute of Technology, Kanpur
'Principles of Database Management is my favorite textbook for
teaching a course on database management. Written in a
well-illustrated style, this comprehensive book covers essential
topics in established data management technologies and recent
discoveries in data science. With a nice balance between theory and
practice, it is not only an excellent teaching medium for students
taking information management and/or data analytics courses, but
also a quick and valuable reference for scientists and engineers
working in this area.' Chuan Xiao, Graduate School of Informatics,
Nagoya University
'Data science success stories and big data applications are only
possible because of advances in database technology. This book
provides both a broad and deep introduction to databases. It covers
the different types of database systems (from relational to noSQL)
and manages to bridge the gap between data modeling and the
underlying basic principles. The book is highly recommended for
anyone that wants to understand how modern information systems deal
with ever-growing volumes of data.' Wil van der Aalst, RWTH Aachen
University
'The database field has been evolving for several decades and the
need for updated textbooks is continuous. Now, this need is covered
by this fresh book by Lemahieu, van den Broucke and Baesens. It
spans from traditional topics - such as the relational model and
SQL - to more recent topics – such as distributed computing with
Hadoop and Spark as well as data analytics. The book can be used as
an introductory text and for graduate courses.' Yannis
Manolopoulos, Data Science & Engineering Lab, Aristotle University
of Thessaloniki
'I like the way the book covers both traditional database topics
and newer material such as big data, No-SQL databases, and data
quality. The coverage is just right for my course and the level of
the material is very appropriate for my students. The book also has
clear explanations and good examples.' Barbara Klein, University of
Michigan
This book provides a unique perspective on database management and
how to store, manage, and analyze small and big data. The
accompanying exercises and solutions, cases, slides, and YouTube
lectures turn it into an indispensable resource for anyone teaching
an undergraduate or postgraduate course on the topic.' Wolfgang
Ketter, Erasmus University Rotterdam
'This is a very modern textbook that fills the needs of current
trends without sacrificing the need to cover the required database
management systems fundamentals.' George Dimitoglou, Hood College,
Maryland
'This book is a much needed foundational piece on data management
and data science. The authors successfully integrate the fields of
database technology, operations research and big data analytics,
which have often been covered independently in the past. A key
asset is its didactical approach that builds on a rich set of
industry examples and exercises. The book is a must-read for all
scholars and practitioners interested in database management, big
data analytics and its applications.' Jan Mendling, Institute for
Information Business, Vienna
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