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New Book: Principles of Database Management

The Practical Guide to Storing, Managing and Analyzing Big and Small Data — Cambridge University Press.

This comprehensive textbook teaches the fundamentals of database design, modeling, systems, data storage, and the evolving world of data warehousing, governance and more. Written by experienced educators and experts in big data, analytics, data quality, and data integration, it provides an up-to-date approach to database management. This full-color, illustrated text has a balanced theory-practice focus, covering essential topics, from established database technologies to recent trends, like Big Data, NoSQL, and more. Fundamental concepts are supported by real-world examples, query and code walkthroughs, and figures, making it perfect for introductory courses for advanced undergraduates and graduate students in information systems or computer science.



Principles of Database Management provides readers with the comprehensive database management information to understand and apply the fundamental concepts of database design and modeling, database systems, data storage, and the evolving world of data warehousing, governance and more. Designed for those studying database management for information management or computer science, this well-illustrated textbook has a well-balanced theory-practice focus and covers the essential topics, from established database technologies up to recent trends like Big Data, NoSQL, and analytics. On-going case studies, drill-down boxes that reveal deeper insights on key topics, retention questions at the end of every section of a chapter, and connections boxes that show the relationship between concepts throughout the text are included to provide the practical tools to get started in database administration.

Given the above considerations, the key distinctive features of our book are:

  • Full-color illustrations throughout the text
  • Extensive coverage of important trending topics, including data warehousing, business intelligence, data integration, data quality, data governance, Big Data, and analytics
  • An online playground with diverse environments, including MySQL for querying; MongoDB; Neo4j Cypher; and a tree structure visualization environment
  • Hundreds of examples to illustrate and clarify the concepts discussed that can be reproduced on the book’s companion online playground
  • Case studies, review questions, problems, and exercises in every chapter
  • Additional cases, problems, and exercises in the appendix

Target audience

The target audience of our book consists of:

  • Under- or postgraduate students taking courses on database management in BSc and MSc programmes on Information Management and/or Computer Science
  • Business professionals who would like to refresh or update their knowledge on database management
  • Database administrators, database developers or database programmers interested in new developments in the area

The book can also be used by tutors in courses such as the following:

  • Principles of Database Management
  • Database Modelling
  • Database Systems
  • Data Management
  • Data Modelling

It can also be useful to universities working out degrees in e.g. Big Data & Analytics and Data Science.

Table of contents

Part 1: Databases and Database Design
  • Chapter 1: Fundamental Concepts of Database Management (Show/hide details)
  • Chapter 2: Architecture and Categorization of DBMSs (Show/hide details)
  • Chapter 3: Conceptual Data Modeling (Show/hide details)
  • Chapter 4: Organizational Aspects of Data Management (Show/hide details)
Part 2: Types of Database Systems
  • Chapter 5: Legacy Databases (Show/hide details)
  • Chapter 6: Relational Databases: The Relational Model (Show/hide details)
  • Chapter 7: Relational Databases: Structured Query Language (SQL) (Show/hide details)
  • Chapter 8: Object Oriented Databases and Object Persistence (Show/hide details)
  • Chapter 9: Extended Relational Databases (Show/hide details)
  • Chapter 10: XML Databases (Show/hide details)
  • Chapter 11: NoSQL Databases (Show/hide details)
Part 3: Physical Data Storage, Transaction Management and Database Access
  • Chapter 12: Physical File Organization and Indexing (Show/hide details)
  • Chapter 13: Physical Database Organization (Show/hide details)
  • Chapter 14: Basics of Transaction Management (Show/hide details)
  • Chapter 15: Accessing Databases and Database APIs (Show/hide details)
  • Chapter 16: Data Distribution and Distributed Transaction Management (Show/hide details)
Part 4: Data Warehousing, Data Governance and (Big) Data Analytics
  • Chapter 17: Data Warehousing and Business Intelligence (Show/hide details)
  • Chapter 18: Data Integration, Data Quality and Data Governance (Show/hide details)
  • Chapter 19: Big Data (Show/hide details)
  • Chapter 20: Analytics (Show/hide details)

About the authors

Wilfried Lemahieu is a professor at KU Leuven, 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 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. See feb.kuleuven.be/wilfried.lemahieu for further details.

Bart Baesens is a professor of Big Data and Analytics at KU Leuven (Belgium) and a lecturer at the University of Southampton (United Kingdom). He has done extensive research on Big Data & Analytics, Credit Risk Modeling, Fraud Detection and Marketing Analytics. He wrote 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 (Oxford University Press, 2009), Analytics in a Big Data World (Wiley, 2014), Beginning Java Programming (Wiley, 2015), Fraud Analytics using Descriptive, Predictive and Social Network Techniques (Wiley, 2015), Credit Risk Analytics (Wiley, 2016) and Profit-Driven Business Analytics (Wiley, 2017). He sold more than 15.000 copies of these books worldwide, some of which have been translated in Chinese, Russian and Korean. His research is summarized atwww.dataminingapps.com. He also regularly tutors, advises and provides consulting support to international firms with respect to their big data, analytics and credit risk management strategy.

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 (Wiley, 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. See seppe.net for further details.

The book is available from this website

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