Database Concepts

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Hands-on exploration of database fundamentals Database Concepts offers students practical help creating and managing small databases, from two of the world’s leading database authorities. The text focuses on database concepts, rather than features and functions of a particular product, making it flexible enough to work with the instructor’s preferred software. Data sets for three sample databases run throughout portions of the text so students can practice working with complete databases. Three running projects challenge learners to apply concepts and techniques to real business situations. In the 9th edition, Microsoft® Office 2019, and particularly Microsoft Access™ 2019, is now the basic software used and is shown running on Microsoft Windows™ 10. Also available as an easy-to-use, standalone Pearson eText Pearson eText is a simple-to-use, mobile-optimized, personalized reading experience that can be adopted on its own as the main course material. It lets students highlight, take notes, and review key vocabulary all in one place, even when offline. Seamlessly integrated videos and other rich media engage students and give them access to the help they need, when they need it. Educators can easily customize the table of contents and share their own notes with students so they see the connection between their eText and what they learn in class — motivating them to keep reading, and keep learning.

Author(s): David M. Kroenke, David J. Auer, Scott L. Vandenberg, Robert C. Yoder
Edition: 9
Publisher: Pearson
Year: 2020

Language: English
Pages: 552
City: New York

PART 1: DATABASE FUNDAMENTALS
1. Getting Started
2. The Relational Model
3. Structured Query Language

PART 2: DATABASE DESIGN
4. Data Modeling and the Entity-Relationship Model
5. Database Design

PART 3: DATABASE MANAGEMENT
6. Database Administration
7. Data Warehouses, Business Intelligence Systems, and Big Data

ONLINE EXTENSIONS
Extension A: Working with MySQL
Extension B: Advanced SQL
Extension C: Advanced Business Intelligence and Big Data