Chapter 4The Database Management System Concept Fundamentals of Database Management Systems by Mark L. Gillenson, Ph.D. University of Memphis Presentation by: Amita Goyal Chin, Ph.D. Virginia Commonwealth University John Wiley & Sons, Inc.
Chapter Objectives • Discuss the problems encountered in a nondatabase information systems environment. • List the five basic principles of the database concept. • Describe how data can be considered to be a manageable resource.
Chapter Objectives • List the three problems created by data redundancy. • Describe the nature of data redundancy among many files. • Explain the relationship between data integration and data redundancy in one file.
Chapter Objectives • State the primary defining feature of a database management system. • Explain why the ability to store multiple relationships is an important feature of the database approach.
Chapter Objectives • Explain why providing support for such control issues as data security, backup and recovery, and concurrency is an important feature of the database approach. • Explain why providing support for data independence is an important feature of the database approach.
Data Processing Systems • Data was stored in different formats in different files. • Data was often not shared among different programs that needed it, necessitating the duplication of data in redundant files. • Little was understood about file design, resulting in redundant data within individual files.
Data Processing Systems • Files often could not be rebuilt after being damaged by a software error or a hardware failure. • Data was not secure and was vulnerable to theft or malicious mischief by people inside or outside of the company.
Data Processing Systems • Programs were usually written in such a manner that if the way that the data was stored changed, the program had to be modified to continue working. • Changes in everything from access methods to tax tables required programming changes.
The Database Concept • 1. Data as a Manageable Resource • 2. Data Integration and Data Redundancy • 3. Multiple Relationships • 4. Data Control Issues • 5. Data Independence
The Database Concept • Data as a Manageable Resource - The creation of a data-centric environment in which a company’s data can truly be thought of as a significant corporate resource. A key feature of this environment is the ability to share data among those inside and outside of the company who require access to it.
The Database Concept • Data Integration and Data Redundancy - The ability to achieve data integration while at the same time storing data in a nonredundant fashion. This, alone, is the central, defining feature of the database approach. • Multiple Relationships - The ability to store data representing entities involved in multiple relationships without introducing data redundancy or other structural problems.
The Database Concept • Data Control Issues - The establishment of an environment that manages certain data control issues, such as data security, backup and recovery, and concurrency control. • Data Independence - The establishment of an environment that permits a high degree of data independence.
Data as a Manageable Resource • Information systems environment: • Hardware • Networks • Applications software • Systems software • People • Data
Data as a Manageable Resource • Historically, data has not been the highest priority concern. • As the operational, tactical, and strategic corporate levels became more dependent on information systems, data increasingly became recognized as an important corporate resource.
Data as a Manageable Resource • The corporate community became increasingly convinced that a firm’s data could provide a significant competitive advantage to the firm. • It became clear that data would have to be managed in an organized way.
Data as a Manageable Resource • Needed a software utility that could manage and protect data. • Data could be a critical corporate resource. • Out of this need was born the database management system.
Data as a Manageable Resource • Reengineering - data is aggressively used to redesign business processes. • Electronic commerce - a database at the heart of every web site; allows companies and customers to conduct business. • ERP systems - collections of application programs build around a central database.
Data Integration and Data Redundancy • Data integration - the ability to tie together pieces of related data within an information system. • Data redundancy - the same fact about the business environment is stored more than once within an information system.
Data Redundancy - Problems • Redundant data takes up a great deal of extra disk space. • If the redundant data has to be updated, it takes additional time to do so. This can be a major performance issue. • There is the potential for data integrity problems.
Data Integrity • Refers to the accuracy of the data. • Inaccurate data leaves the whole information system of limited value.
Data Redundancy,Data Integrity • When all copies of redundant data are not updated consistently, a data integrity problem exists.
Anomalies • Typically occur in poorly structured files. • Problems arise when two different kinds of data, like salesperson and customer data are merged into one file.
Anomalies • Deletion Anomaly - e.g, if you delete a customer and that record was the only one for a salesperson, the salesperson’s data is gone. • Insertion Anomaly - e.g., General Hardware cannot add data about a new salesperson the company just hired until she is assigned at least one customer. • Update Anomaly - redundant data in the database file must be updated each place it exists when it changes
Database Management System • A software utility for storing and retrieving data that gives the end-user the impression that the data is well integrated even though the data can be stored with no redundancy at all.
Data Control Issues • Data security • Backup and Recovery • Concurrency Control
Computer Security • A very broad topic • Protecting the physical hardware environment • Defending against hacker attacks • Encrypting data transmitted over networks • Educating employees on the importance of protecting the company’s data • … and many more
Backup and Recovery • Data can be lost or corrupted in any of a variety of ways: • a disaster such as a fire, a hurricane, or an earthquake • hackers • computer viruses • poorly written application programs • unintentional error
Concurrency Problem • Updates to a database can interfere with each other in such a way that the resulting data values will be incorrect. • A database management system must be designed to protect its databases from such an eventuality.
Data Independence • Data Dependence - if for any reason the storage characteristics of the data had to be changed, the application program itself had to be modified, often extensively. • Data Independence - to have a data storage and programming environment in which as many types of changes in the data structure as possible would not require changes in the application programs that use them.
Major DBMS Approaches • Hierarchical - navigational • Network - navigational • Relational - became commercially viable in about 1980. • Object-oriented - useful for a variety of niche applications.
Hierarchical & Network • Called navigational approaches because of the way that programs have to “navigate” through hierarchies and networks of data to find needed data. • Developed in the 1960s and • Somewhat similar in structure
Hierarchical & Network • Suitable only for mainframe computers • were an elegant solution to the redundancy/integration problem at the time • Complex, difficult to work • Now considered legacy systems
Relational Database • Became commercially viable in about 1980 • Soon became the preferred DBMS approach and it has remained so ever since.
Object-oriented • Has proven useful for a variety of niche applications • It is interesting to note that some of the key object-oriented database concepts have found their way into some of the mainstream relational DBMSs and some are described as taking a hybrid object/relational approach to database.
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