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Unit 1: Background and Terminology Chapters 1 + 2: Modern Database Management 9th Edition Jeffrey A. Hoffer, Mary B. Prescott, Heikki Topi © 2009 Pearson Education, Inc. Publishing as Prentice Hall 1 Definitions Database: organized collection of logically related data Data: stored representations of meaningful objects and events Structured: numbers, text, dates Unstructured: images, video, documents Information: data processed to increase knowledge in the person using the data Metadata: data that describes the properties and context of user data Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 2 Figure 1-1a Data in context Context helps users understand data Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 3 Figure 1-1b Summarized data Graphical displays turn data into useful information that managers can use for decision making and interpretation Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 4 Descriptions of the properties or characteristics of the data, including data types, field sizes, allowable values, and data context Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 5 Figure 11-6 Example of DBMS log entry Data Characteristics Status vs. Event Data Status Event = a database action (create/update/delete) that results from a transaction Status Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 6 Figure 11-7 Transient operational data Data Characteristics Transient vs. Periodic Data With transient data, changes to existing records are written over previous records, thus destroying the previous data content7 Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Figure 11-8 Periodic warehouse data Data Characteristics Transient vs. Periodic Data Periodic data are never physically altered or deleted once they have been added to the store Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 8 Derived Data Data that can be computed as opposed to stored facts. Objectives Ease of use for decision support applications Fast response to predefined user queries Customized data for particular target audiences Ad-hoc query support Data mining capabilities Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 9 Duplicate Data 10 Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Disadvantages of File Processing Program-Data Dependence Duplication of Data No centralized control of data Lengthy Development Times Different systems/programs have separate copies of the same data Limited Data Sharing All programs maintain metadata for each file they use Programmers must design their own file formats Excessive Program Maintenance 80% of information systems budget Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 11 Problems with Data Dependency Each application programmer must maintain his/her own data Each application program needs to include code for the metadata of each file Each application program must have its own processing routines for reading, inserting, updating, and deleting data Lack of coordination and central control Non-standard file formats Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 12 Problems with Data Redundancy Waste of space to have duplicate data Causes more maintenance headaches The biggest problem: Data changes in one file could cause inconsistencies Compromises in data integrity Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 13 SOLUTION: The DATABASE Approach Central repository of shared data Data is managed by a controlling agent Stored in a standardized, convenient form Requires a Database Management System (DBMS) Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 14 Database Management System A software system that is used to create, maintain, and provide controlled access to user databases Order Filing System Invoicing System Payroll System DBMS Central database Contains employee, order, inventory, pricing, and customer data DBMS manages data resources like an operating system manages hardware resources Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 15 Advantages of the Database Approach Program-data independence Planned data redundancy Improved data consistency Improved data sharing Increased application development productivity Enforcement of standards Improved data quality Improved data accessibility and responsiveness Reduced program maintenance Improved decision support Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 16 Costs and Risks of the Database Approach New, specialized personnel Installation and management cost and complexity Conversion costs Need for explicit backup and recovery Organizational conflict Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 17 Elements of the Database Approach Data models Relational Databases Database technology involving tables (relations) representing entities and primary/foreign keys representing relationships Use of Internet Technology Graphical system capturing nature and relationship of data Enterprise Data Model–high-level entities and relationships for the organization Project Data Model–more detailed view, matching data structure in database or data warehouse Networks and telecommunications, distributed databases, clientserver, and 3-tier architectures Database Applications Application programs used to perform database activities (create, read, update, and delete) for database users Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 18 Figure 1-5 Components of the Database Environment Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 19 Components of the Database Environment CASE Tools–computer-aided software engineering Repository–centralized storehouse of metadata Database Management System (DBMS) –software for managing the database Database–storehouse of the data Application Programs–software using the data User Interface–text and graphical displays to users Data/Database Administrators–personnel responsible for maintaining the database System Developers–personnel responsible for designing databases and software End Users–people who use the applications and databases Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 20 The Range of Database Applications Personal databases Workgroup databases Departmental/divisional databases Enterprise database Enterprise resource planning (ERP) systems Data warehousing implementations Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 21 Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 22 Figure 1-7 Workgroup database with wireless local area network Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 23 Enterprise Database Applications Enterprise Resource Planning (ERP) Integrate all enterprise functions (manufacturing, finance, sales, marketing, inventory, accounting, human resources) Data Warehouse Integrated decision support system derived from various operational databases Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 24 Data Warehousing Data Warehouse: A subject-oriented, integrated, time-variant, nonupdatable collection of data used in support of management decision-making processes Subject-oriented: e.g. customers, patients, students, products Integrated: Consistent naming conventions, formats, encoding structures; from multiple data sources Time-variant: Can study trends and changes Non-updatable: Read-only, periodically refreshed Data Mart: A data warehouse that is limited in scope Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 25 Need for Data Warehousing Integrated, company-wide view of high-quality information (from disparate databases) Separation of operational and informational systems and data (for improved performance) Table 11-1 – Comparison of Operational and Informational Systems Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 26 Figure 1-8 An enterprise data warehouse Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 27 Figure 11-2 Independent data mart data warehousing architecture Data marts: Mini-warehouses, limited in scope L T E Data access complexity Separate ETL for each independent data mart due to multiple data marts Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 28 Figure 11-3 Dependent data mart with operational data store: a three-level architecture ODS provides option for obtaining current data L T E Single ETL for enterprise data warehouse (EDW) Simpler data access Dependent data marts loaded from EDW Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 29 Figure 11-4 Logical data mart and real time warehouse architecture ODS and data warehouse are one and the same L T E Chapter 1 Data marts are NOT separate databases, Near real-time ETL for but logical views of the data warehouse Data Warehouse Easier to create new data marts © 2009 Pearson Education, Inc. Publishing as Prentice Hall 30 Application Logic in C/S Systems Presentation Logic Input–keyboard/mouse Output–monitor/printer GUI Interface Processing Logic I/O processing Business rules Data management Procedures, functions, programs Storage Logic Data storage/retrieval DBMS activities Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 31 Client/Server Architectures Client does extensive processing File Server Architecture Database Server Architecture Three-tier Architecture Client does little processing Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 32 File Server Architecture All processing is done at the PC that requested the data FAT CLIENT Entire files are transferred from the server to the client for processing Problems: Huge amount of data transfer on the network Each client must contain full DBMS Heavy resource demand on clients Client DBMSs must recognize shared locks, integrity checks, etc. Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 33 Figure 9-2 File server model FAT CLIENT Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 34 Two-Tier Database Server Architectures Client is responsible for I/O processing logic Some business rules logic Server performs all data storage and access processing DBMS is only on server Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 35 Three-Tier Architectures GUI interface (I/O processing) Client Application server Database server Business rules Data storage Browser Web Server DBMS Thin Client PC just for user interface and a little application processing. Limited or no data storage (sometimes no hard drive) Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 36 Figure 9-4a Generic three-tier architecture Thinnest clients Business rules on separate server DBMS only on DB server Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 37 Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 38 Common Logic Distributions Figure 9-5a Two-tier clientserver environments Processing logic could be at client, server, or both Figure 9-5b n-tier clientserver environment Processing logic will be at application server or Web server Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 39 Middleware Software that allows an application to interoperate with other software No need for programmer/user to understand internal processing Accomplished via Application Program Interface (API) The “glue” that holds client/server applications together Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 40 Web-Enabled Databases Web applications requiring databases Customer relationship management (CRM) Business-to-consumer (B2C) Electronic data interchange (EDI) Private intranets XML-defined Web services Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 41 Web-Enabled Databases (cont.) Issues to consider Which technologies to use? Security/privacy protection Managing huge volumes of data from Internet transactions Maintaining data quality Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 42 Figure 10-1 Database-enabled intranet/internet environment Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 43 Server-Side Extensions Programs that interact directly with Web servers to handle requests e.g. database-request handling middleware Figure 10-2 Web-to-database middleware Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 44 Figure 10-7 Web services deployment (adapted from Newcomer, 2002) Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 45 Table 1-6 Summary of Database Applications Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 46 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall Chapter 1 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 47