Data Management 5e: Databases and Organizations - Softcover

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Richard T. Watson is currently the J. Rex Fuqua Distinguished Chair for Internet Strategy in the Department of MIS at the University of Georgia's Terry College of Business. He is also the Director of the Center for Information Systems Leadership. Watson received his B Sc and Dip Comp from the University of Western Australia, and he received his Ph.D. from the University of Minnesota. He is a visiting professor at Agder University College(Kristiansand, Norway), and Fudan University (Shanghai, China). Watson has published around 100 refereed articles, written or edited more than 10 books (including a data management textbook). He has served as a senior editor for MIS Quarterly and was co-conference chair forr ICIS2004. He is currently the President of the Association for Information Systems. His current research interests are u-commerce, net-based customer service systems, open source, and information systems leadership. He collaborates with researchers in several countries, including Australia, Brazil, Canada, China, France, Germany, Italy, Norway, and Singapore.

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Wanted: Expert Data Modeling and SQL Skills Inquire Within.

Data modeling and SQL these are the data management skills that are in demand in today s job market. That s why Richard Watson s Fifth Edition of Data Management: Databases and Organizations offers in-depth, fully integrated coverage of data modeling and SQL, and a broad managerial perspective.

Updated with the latest developments in the field, the Fifth Edition will help you design and create relational databases, formulate complex SQL queries, understand OLAP, use SQL with Java, learn how to use XML, and prepare yourself for the real world of data management.

New Features of the Fifth Edition:

• A new chapter on embedded SQL in Java and JDBC
• A section on multidimensional expressions (MDX)
• New material on content management systems (CMS) and wiki technology
• Greater focus on MySQL
• Increased coverage of mandatory and optional elements in data modeling