Watson: Data Management, 6th Edition

Data Management:
Databases and Organizations

Richard T. Watson, University of Georgia

Edition 6.0

Copyright 2016
Publication date: August 28, 2015
Current Version: April 12, 2018

For Instructors

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  • 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.
  • An ebook version is available at Amazon: https://www.amazon.com/dp/B00E8HS8N2

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Paperbacks:
Student Price: $58.50
ISBN: 978-1-943153-03-9
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Description & Features

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.

New for the Sixth Edition:

  • New coverage of on R, data visualization, text mining, clustering computing, and dashboards
  • MySQL Workbench used for data modeling and SQL querying
  • Integration of XML and MySQL

Table of Contents

Section 1: The Managerial Perspective

Ch 1: Managing Data

Ch 2: Information

Section 2: Data Modeling and SQL

Ch 3: The Single Entity

Ch 4: The One-to-Many Relationship

Ch 5: The Many-to-Many Relationship

Ch 6: One-to-One and Recursive Relationships

Ch 7: Data Modeling

Reference 1: Basic Structures

Ch 8: Normalization and Other Data Modeling Methods

Ch 9: The Relational Model and Relational Algebra

Ch 10: SQL

Reference 2: SQL Playbook

Section 3: Advanced Data Management

Ch 11: Spatial and Temporal Data Management

Ch 12: XML: Managing Data Exchange

Ch 13: Organization Intelligence

Ch 14: Introduction to R

Ch 15: Data Visualization

Ch 16: Text Mining and Natural Language Processing

Ch 17: Clustering Computing

Ch 18: Dashboards

Section 4: Managing Organizational Memory

Ch 19: Data Structure and Storage

Ch 20: Data Processing Architectures

Ch 21: SQL and Java

Ch 22: Data Integrity

Ch 23: Data Administration