Data Management

Data Management

Databases and Analytics

Edition 7.0 | Copyright 2023 | Publication Date: October 2022

Richard T. Watson, University of Georgia


Please note: Prospect Press distributes only the print version of this text, and we do not provide review copies. We will provide a printed desk copy to adopters after we receive an order for at least five print copies. The eText version is available for free at the author's website.

This is not your traditional database book. It differs in three fundamental ways. First, it is deeper than most database textbooks in its coverage of data modeling and SQL. Second, the treatments of data modeling and SQL are intertwined because the author’s teaching experience indicates that students more readily understand the intent of data modeling when they grasp the long-term goal— querying a well-designed relational database. Third, the book is broader than most database books, encompassing the design and maintenance of computer-based organization memory.


Deeper Coverage
Delve into data modeling and SQL deeper than in other database books. The market seeks graduates who have these fundamental skills. Also, cover advanced data management topics including R, data visualization, text mining, Hadoop distributed file system (HDFS), MapReduce, XML and organizational intelligence.

Intertwined Presentation of Data Modeling and SQL
Motivate learning about data modeling by teaching about the long-term goal of database management—querying a well-designed relational database.

Table of Contents

Detailed Table of Contents PDF


Section 1 The Managerial Perspective
Chapter 1 Managing Data
Chapter 2 Information

Section 2 Data Modeling and SQL
Chapter 3 The Single Entity
Chapter 4 The One-to-Many Relationship
Chapter 5 The Many-to-Many Relationship
Chapter 6 One-to-One and Recursive Relationships
Chapter 7 Data Modeling
Chapter 8 Normalization and Other Data Modeling Methods
Chapter 9 The Relational Model and Relational Algebra
Chapter 10 SQL

Section 3 Data Science and advanced Data Management
Chapter 11 Spatial and Temporal Data Management
Chapter 12 Graph Databases
Chapter 13 XML: Managing Data Exchange
Chapter 14 Organizational Intelligence
Chapter 15 Introduction to R
Chapter 16 Data visualization
Chapter 17 Text mining & natural language processing
Chapter 18 Cluster computing
Chapter 19 Dashboards

Section 4 Managing Organizational Memory
Chapter 20 Data Structure and Storage
Chapter 21 Data Processing Architectures
Chapter 22 SQL and Java
Chapter 23 Data Integrity
Chapter 24 Data Administration


About the Author

Richard T. Watson is the J. Rex Fuqua Distinguished Chair for Internet Strategy in the Department of MIS at the University of Georgia's Terry College of Business. In 2006, Dr. Watson was appointed a Fellow of the Association for Information Systems and in 2007 a Fellow of the Royal Society of Arts. In 2011, he received the Association for Information Systems' (AIS) LEO award, which is given for exceptional lifetime achievement in Information Systems. He has published over 150 articles in leading academic and practitioner journals; written or edited more than 10 books (including a data Management textbook and the first book on Energy Informatics).  His most recent research focuses on Information Systems (IS) leadership, the business of open source, net-based customer service systems, and the role of IS in creating sustainable business practices as well as ecological sustainability.

Richard T. Watson

Previous Editions

Data Management: Databases and Organizations

Data Management: Databases and Organizations

Richard T. Watson, University of Georgia

Edition 6.0
Copyright 2016
Publication date: April 01, 2018

View Previous Edition


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