Chapter 5 Lecture 2. Principles of Information Systems2 Objectives Understand Data definition...

Chapter 5 Lecture 2

Principles of Information Systems 2

Objectives

• Understand Data definition language (DDL) and data dictionary

• Learn about popular DBMSs

• Understand types of Data Warehouses

• Conceptually understand ODBC

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Creating and Modifying the Database

• Data definition language (DDL)

• A collection of instructions and commands used to define and describe data and data relationships in a specific database

• Allows the database’s creator to describe the data and the data relationships that are to be contained in the schema and subschemas

• Data dictionary: a detailed description of all the data used in the database

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Figure 5.11: Using a Data Definition Language to Define a Schema

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Figure 5.12: A Typical Data Dictionary Entry

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Storing and Retrieving Data

• When an application program request data from DBMS, the application program follows a logical access path

• When the DBMS goes to a storage device to retrieve the requested data, it follows a path to the physical location (physical access path) where the data is stored

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Figure 5.13: Logical and Physical Access Paths

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Manipulating Data and Generating Reports

• Data manipulation language (DML): the commands that are used to manipulate the data in a database

• Structured Query Language (SQL): adopted by the American National Standards Institute (ANSI) as the standard query language for relational databases

• Once a database has been set up and loaded with data, it can produce reports, documents, and other outputs

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Table 5.6: Examples of SQL Commands

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Popular Database Management Systems

• Popular DBMSs for end users include Microsoft’s Access and Corel’s Paradox

• The complete database management software market includes databases by IBM, Oracle, and Microsoft

• Examples of open-source database systems: PostgreSQL and MySQL

• Many traditional database programs are now available on open-source operating systems

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Selecting a Database Management System

• Important characteristics of databases to consider:

• Size of the database

• Number of concurrent users

• Performance

• The ability of the DBMS to be integrated with other systems

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Selecting a Database Management System (continued)

• Important characteristics of databases to consider (continued):

• Features of the DBMS

• Vendor considerations

• Cost of the system

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Database Applications: Linking the Company Database to the Internet

• Corporate databases can be accessed by customers, suppliers, and company employees through:

• The Internet

• Intranets

• Extranets

• Semantic Web: a seamless integration of traditional databases with the Internet

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Data Warehouses, Data Marts, and Data Mining

• Data warehouse: a database that collects business information from many sources in the enterprise, covering all aspects of the company’s processes, products, and customers

• Data mart: a subset of a data warehouse

• Data mining: an information-analysis tool that involves the automated discovery of patterns and relationships in a data warehouse

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Figure 5.17: Elements of a Data Warehouse

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Table 5.8: Common Data-Mining Applications

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Business Intelligence

• Business intelligence (BI): the process of gathering enough of the right information in a timely manner and usable form and analyzing it to have a positive impact on business strategy, tactics, or operations

• Knowledge management: the process of capturing a company’s collective expertise wherever it resides and distributing it wherever it can help produce the biggest payoff

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Distributed Databases

• Distributed database

• A database in which the data may be spread across several smaller databases connected via telecommunications devices

• Corporations get more flexibility in how databases are organized and used

• Replicated database: a database that holds a duplicate set of frequently used data

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Online Analytical Processing (OLAP)

• Software that allows users to explore data from a number of different perspectives

Table 5.9: Comparison of OLAP and Data Mining

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Open Database Connectivity (ODBC)

• Standards that ensure that software can be used with any ODBC-compliant database

• Can be used to export, import, or link tables between different applications

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Figure 5.19: Advantages of ODBC

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Object-Oriented and Object-Relational Database Management Systems

• Object-oriented database

• Stores both data and its processing instructions

• Method: a procedure or action

• Message: a request to execute or run a method

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Object-Oriented and Object-Relational Database Management Systems

(continued)

• Object-oriented database management system (OODBMS): group of programs that manipulate an object-oriented database and provide a user interface and connections to other application programs

• Object-relational database management system (ORDBMS): DBMS capable of manipulating audio, video, and graphical data

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Summary

• Hierarchy of data: bits, characters, fields, records, files, and databases

• Entity: a generalized class of things (objects) for which data is collected, stored, and maintained

• Attribute: characteristic of an entity

• Data model: diagram of entities and relationships

• Relational model: describes data in which all elements are placed in two-dimensional tables called relations

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Summary (continued)

• Selecting: eliminates rows according to certain criteria

• Projecting: eliminates columns in a table

• Database management system (DBMS): group of programs used as an interface

• Between a database and application programs

• Database and the user

• Data dictionary: detailed description of all the data used in the database

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Summary (continued)

• Data warehouse: database that collects business information from all aspects of a company’s processes, products, and customers

• Data mining: an information-analysis tool for the automated discovery of patterns and relationships in a data warehouse

• Open database connectivity (ODBC) standards: ensure that software can be used with any ODBC-compliant database