This is not your traditional database textbook. It differs in three fundamental ways.
First, it is deeper than most database books in its coverage of data modeling and SQL. The market seeks graduates who have these fundamental skills. Time and again, students who have completed my data management class have told me how these skills have been invaluable in their first and subsequent jobs. The intention is to place great emphasis on the core skills of data management. The consequence is that there is a better match between the skills students develop and those the market needs. This means that students find this text highly relevant.
Second, the treatments of data modeling and SQL are intertwined because my database 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. The double helix, upward, intertwined, spiraling of data modeling and SQL is a unique pedagogical feature. Classroom testing indicates it is a superior method of teaching compared to handling data modeling and SQL separately. Students quickly understand the reason for data modeling and appreciate why it is a valuable skill. Also, rapid exposure to SQL means students gain hands-on experience that more quickly.
Third, the book is broader than most database books. Databases are one component of an expansive organizational memory. Information systems professionals need to develop a wide perspective of data management if they are to comprehend fully the organizational role of information systems.
In essence, the book is deeper where it matters—data modeling and SQL—and broader to give students a managerial outlook and an understanding of the latest technological advancements.
Information is a key resource for modern organizations. It is a critical input to managerial tasks. Because managers need high-quality information to manage change in a turbulent, global environment, many organizations have established systems for storing and retrieving data, the raw material of information. These storage and retrieval systems are an organization's memory. The organization relies on them, just as individuals rely on their personal memory, to be able to continue as a going concern.
The central concern of information systems management is to design, build, and maintain information delivery systems. Information systems management needs to discover its organization's information requirements so that it can design systems to serve these needs. It must merge a system's design and information technology to build applications that provide the organization with data in a timely manner, appropriate formats, and at convenient locations. Furthermore, it must manage applications so they evolve to meet changing needs, continue to operate under adverse conditions, and are protected from unauthorized access.
An information delivery system has two components: data and processes. This book concentrates on data, which is customarily thought of as a database. I deliberately set out to extend this horizon, however, by including all forms of organizational data stores because I believe students need to understand the role of data management that is aligned with current practice. In my view, data management is the design and maintenance of computer-based organizational memory. Thus, you will find chapters on XML and organizational intelligence technologies.
The decision to start the book with a managerial perspective arises from the belief that successful information systems practice is based on matching managerial needs, social system constraints, and technical opportunities. I want readers to appreciate the big picture before they become immersed in the intricacies of data modeling and SQL.
The first chapter introduces the case study, The Expeditioner, which is used in most of the subsequent chapters to introduce the key themes discussed. Often it sets the scene for the ensuing material by presenting a common business problem.
The second section of the book provides in-depth coverage of data modeling and SQL. Data modeling is the foundation of database quality. A solid grounding in data modeling principles and extensive practice are necessary for successful database design. In addition, this section exposes students to the full power of SQL.
I intend this book to be a long-term investment for students. There are useful reference sections for data modeling and SQL. The data modeling section details the standard structures and their relational mappings. The SQL section contains an extensive list of queries that serves as a basis for developing other SQL queries. The purpose of these sections is to facilitate pattern matching. For example, a student with an SQL query that is similar to a previous problem can rapidly search the SQL reference section to find the closest match. The student can then use the model answer as a guide to formulating the SQL query for the problem at hand. These reference sections are another unique teaching feature that will serve students well during the course and in their careers.
This 6th edition is a substantial revision in that it adds new chapters to provide an introduction to R, a statistics and graphics package, which provides the foundation necessary for the new chapters on data visualization, text mining, and Hadoop distributed file system (HDFS) and MapReduce. These additions provide today’s students with the skills they need to work in topical areas such as social media analytics and big data. These chapters are included in the third section, now titled Advanced Data Management, which also covers spatial and temporal data, XML, and organizational intelligence.
The fourth and final section examines the management of organizational data stores. It covers data structures and storage, data processing architectures, SQL and Java, data integrity, and data administration.
A student completing this text will
This edition has the following improvements and additions.
Richard T. Watson
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