Database Systems: Introduction to Databases and Data Warehouses

Database Systems: Introduction to Databases and Data Warehouses

Edition 1.0 | Copyright 2017 | Publication Date: June 2016

Nenad Jukić, Loyola University Chicago
Susan Vrbsky, The University of Alabama

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Overview


Designed for introductory use in undergraduate and graduate information systems database courses, this comprehensive text requires no prerequisites. The goal of its lessons are to provide a significant and foundational level of database expertise to students. This edition was formerly published by Pearson Education, Inc, and is identical to that text except for some minor corrections.

Features


(Click HERE for full Preface)

Cover Both Operational and Analytical Database Systems

Teach students to design and use operational and analytical databases applicable to today’s business environments.

Learning Through Exploration

Use meaningful hands-on experiences to create a theoretical foundation of key concepts.

Includes Web-Based Data Modeling Suite

Have your students create ER diagrams, relational schemas, and dimensional models (star schemas.) using employ the free Web-based data modeling suite ERDPlus designed and developed in conjunction with the text.

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Table of Contents


Detailed Table of Contents PDF
  • Chapter 1: Introduction

  • Part 1: Operational Databases
  • Chapter 2: Database Requirements and ER Modeling
  • Chapter 3: Relational Database Modeling
  • Chapter 4: Update Operations, Update Anomalies, and Normalization
  • Chapter 5: SQL
  • Chapter 6: Database Implementation and Use

  • Part 2: Analytical Databases
  • Chapter 7: Data Warehousing Concepts
  • Chapter 8: Data Warehouse and Data Mart Modeling
  • Chapter 9: Data Warehouse Implementation and Use

  • Part 3: Other Topics
  • Chapter 10: Overview of DBMS Functionalities and Database Administration

  • Appendices:
  • Appendix A: Enhanced ER
  • Appendix B: Further Notes on Normalization and Higher Normal Forms
  • Appendix C: Enterprise Resource Planning (ERP)
  • Appendix D: Data Governance and Master Data Management
  • Appendix E: Object-Oriented Databases
  • Appendix F: Distributed Databases, Parallel Databases, and Cloud Computing
  • Appendix G: Data Mining
  • Appendix H: XML
  • Appendix I: NOSQL Databases
  • Appendix J: Big Data

About the Authors


Svetlozar Evtimov Nestorov is a senior researcher at the Computation Institute and teaches in the Department of Computer Science at the University of Chicago. His research and his courses focus on data mining, data warehousing, and web technologies.


Nenad Jukić teaches undergraduate, graduate, and executive and professional education classes at the Quinlan School of Business of Loyola University of Chicago. His classes cover databases, data warehousing, business intelligence, computer programming, business computer applications, and health care information systems. Dr. Jukić was named Loyola’s Faculty Member of the Year, Quinlan’s Outstanding Undergraduate Teacher of the Year and has twice been recognized as Quinlan’s top researcher. His research focuses on database modeling and management, data warehousing, business intelligence, data mining, business analytics, Big Data, e-business, and IT strategy.


Susan V. Vrbsky is an associate professor and interim department head of Computer Science at the University of Alabama. Dr. Vrbsky is the director of the Cloud and Cluster Computing Laboratory. Her research has explored topics including data intensive computing, real-time databases, database security, mobile databases, and green computing. She has co-authored over 100 peer-reviewed publications.


Instructor Resources


Prospect Press provides instructors with an instructor manual, lecture slides and a test bank for each title.
Some texts have additional resources including case teaching notes, tutorials, and addenda.
This content is available to instructors only and is password protected.

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