Abstract

End-to-end coverage starting with legacy technologies to emerging trends such as big data, NoSQL databases, analytics, and data governance. A unique perspective on how lessons learnt from past data management could be relevant in today's technology setting (e.g., navigational access and its perils in Codasyl and XML/OO databases). A critical reflection and accompanying risk management considerations when implementing the technologies considered, based on our own experiences from participating in data and analytics-related projects with industry partners in a variety of sectors, from banking to retail and from government to the cultural sector. Offering a solid balance between theory and practice, including various exercises, industry examples, and case studies originating from a diversified and complementary business practice, scientific research, and academic teaching experience
Under- or postgraduate students taking courses on database management in BSc and MSc programs in information management and/or computer science. Business professionals who would like to refresh or update their knowledge on database management. Information architects, database designers, data owners, data stewards, database administrators, or data scientists interested in new developments in the area.
Thanks to the exercises and industry examples throughout the chapters, the book can also be used by tutors in courses such as: principles of database management, database modeling, database design, database systems, data management, data modeling, and data science. It can also be useful to universities working out degrees in, for example, big data and analytics.
Part 2 (Chapters 5–11) then takes a deep dive into the various types of databases, from legacy prerelational and relational database management systems into more recent approaches such as object-oriented, object-relational, and XML-based databases in Chapters 8, 9, and 10, ending with a solid and up-to-date overview of NoSQL technologies in Chapter 11. This part also includes a comprehensive overview of the SQL in Chapter 7.
In part 3, physical data storage, transaction management, and database access are discussed in depth. Chapter 12 discusses physical file organization and indexing, whereas Chapter 13 elaborates on physical database organization and business continuity. This is followed by an overview on the basics of transaction management in Chapter 14. Chapter 15 introduces database access mechanisms and various database application programming interfaces. Chapter 16 concludes this part by zooming in on data distribution and distributed transaction management.
Chapters 17 to 20 form the last part of this book, where we zoom out and elaborate on data warehousing and emerging interest areas such as data governance, big data, and analytics. Chapter 17 discusses data warehouses and business intelligence in depth, with Chapter 18 discussing managerial concepts such as data integration, data quality, and data governance. Chapter 19 provides an in-depth overview of big data and shows how a solid database setup can make up the cornerstone of a modern analytical environment. Chapter 20 concludes this part and the book by zooming into different types of analytics.
Two appendices are included: one containing an examination bank of questions and the other outlining the on-line playground environment.
A website with additional information (e.g., on-line appendices, additional exercises and case studies, endorsements, and press coverage): (www.pdbmbook.com). Free YouTube lectures for each of the 20 chapters, see (https://www.youtube.com/watch?v=o36Z_OqC2ac&list=PLdQddgMBv5zHcEN9RrhADq3CBColhY2hl). PowerPoint slides for each of the 20 chapters, see (www.pdbmbook.com/lecturers). A solutions manual with the solutions to all multiple choice and open questions. An online playground with diverse environments, including MySQL for querying; MongoDB; Neo4 j Cypher; and a tree structure visualization environment. 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. 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.
