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Traditional File Concepts.ppt
1.
7.1 © 2006
by Prentice Hall Traditional File Concepts
2.
7.2 © 2006
by Prentice Hall • Describe basic file organization concepts and the problems of managing data resources in a traditional file environment • Describe how a database management system organizes information and compare the principal database models • Apply important database design principles OBJECTIVES
3.
7.3 © 2006
by Prentice Hall • Evaluate new database trends • Identify the challenges posed by data resource management and management solutions OBJECTIVES (Continued)
4.
7.4 © 2006
by Prentice Hall • Challenge: Fragmented and isolated corporate systems creating a single integrated view of customers and operations • Solution: single integrated corporate data warehouse, using a single data model. • Oracle 9i database provides near real-time access to customer activity, customer profitability, and customer reactions • Illustrates the importance of managing data resources for achieving profitability Virgin Mobile Australia Case
5.
7.5 © 2006
by Prentice Hall File Organization Terms and Concepts • Bit: Smallest unit of data; binary digit (0,1) • Byte: Group of bits that represents a single character • Field: Group of words or a complete number • Record: Group of related fields • File: Group of records of same type ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT
6.
7.6 © 2006
by Prentice Hall • Database: Group of related files • Entity: Person, place, thing, event about which information is maintained • Attribute: Description of a particular entity • Key field: Identifier field used to retrieve, update, sort a record ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT File Organization Terms and Concepts (Continued)
7.
7.7 © 2006
by Prentice Hall ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT The Data Hierarchy Figure 7-1
8.
7.8 © 2006
by Prentice Hall ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT Entities and Attributes Figure 7-2
9.
7.9 © 2006
by Prentice Hall Problems with the Traditional File Environment Data Redundancy and Inconsistency: • Data redundancy: The presence of duplicate data in multiple data files so that the same data are stored in more than one place or location • Data inconsistency: The same attribute may have different values. ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT
10.
7.10 © 2006
by Prentice Hall • The coupling of data stored in files and the specific programs required to update and maintain those files such that changes in programs require changes to the data Lack of flexibility: • A traditional file system can deliver routine scheduled reports after extensive programming efforts, but it cannot deliver ad-hoc reports or respond to unanticipated information requirements in a timely fashion. ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT Program-data dependence: Problems with the Traditional File Environment (Continued)
11.
7.11 © 2006
by Prentice Hall • Because there is little control or management of data, management will have no knowledge of who is accessing or even making changes to the organization’s data. Lack of data sharing and availability: • Information cannot flow freely across different functional areas or different parts of the organization. Users find different values of the same piece of information in two different systems, and hence they may not use these systems because they cannot trust the accuracy of the data. ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT Poor security: Problems with the Traditional File Environment (Continued)
12.
7.12 © 2006
by Prentice Hall ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT Traditional File Processing Figure 7-3
13.
7.13 © 2006
by Prentice Hall Database Management System (DBMS) • Software for creating and maintaining databases • Permits firms to rationally manage data for the entire firm • Acts as interface between application programs and physical data files • Separates logical and design views of data • Solves many problems of the traditional data file approach THE DATABASE APPROACH TO DATA MANAGEMENT
14.
7.14 © 2006
by Prentice Hall The Contemporary Database Environment THE DATABASE APPROACH TO DATA MANAGEMENT Figure 7-4
15.
7.15 © 2006
by Prentice Hall Components of DBMS: • Data definition language: Specifies content and structure of database and defines each data element • Data manipulation language: Used to process data in a database • Data dictionary: Stores definitions of data elements and data characteristics THE DATABASE APPROACH TO DATA MANAGEMENT
16.
7.16 © 2006
by Prentice Hall Sample Data Dictionary Report THE DATABASE APPROACH TO DATA MANAGEMENT Figure 7-5
17.
7.17 © 2006
by Prentice Hall Types of Databases: • Relational DBMS • Hierarchical and network DBMS • Object-oriented databases THE DATABASE APPROACH TO DATA MANAGEMENT
18.
7.18 © 2006
by Prentice Hall Relational DBMS: • Represents data as two-dimensional tables called relations • Relates data across tables based on common data element • Examples: DB2, Oracle, MS SQL Server THE DATABASE APPROACH TO DATA MANAGEMENT
19.
7.19 © 2006
by Prentice Hall The Relational Data Model THE DATABASE APPROACH TO DATA MANAGEMENT Figure 7-6
20.
7.20 © 2006
by Prentice Hall Three Basic Operations in a Relational Database: • Select: Creates subset of rows that meet specific criteria • Join: Combines relational tables to provide users with information • Project: Enables users to create new tables containing only relevant information THE DATABASE APPROACH TO DATA MANAGEMENT
21.
7.21 © 2006
by Prentice Hall The Three Basic Operations of a Relational DBMS THE DATABASE APPROACH TO DATA MANAGEMENT Figure 7-7
22.
7.22 © 2006
by Prentice Hall Hierarchical and Network DBMS • Organizes data in a tree-like structure • Supports one-to-many parent-child relationships • Prevalent in large legacy systems THE DATABASE APPROACH TO DATA MANAGEMENT Hierarchical DBMS:
23.
7.23 © 2006
by Prentice Hall A Hierarchical Database for a Human Resources System THE DATABASE APPROACH TO DATA MANAGEMENT Figure 7-8
24.
7.24 © 2006
by Prentice Hall Hierarchical and Network DBMS • Depicts data logically as many-to-many relationships THE DATABASE APPROACH TO DATA MANAGEMENT Network DBMS:
25.
7.25 © 2006
by Prentice Hall The Network Data Model Figure 7-9 THE DATABASE APPROACH TO DATA MANAGEMENT
26.
7.26 © 2006
by Prentice Hall Hierarchical and Network DBMS • Outdated • Less flexible compared to RDBMS • Lack support for ad-hoc and English language- like queries Disadvantages: THE DATABASE APPROACH TO DATA MANAGEMENT
27.
7.27 © 2006
by Prentice Hall • Object-oriented DBMS: Stores data and procedures as objects that can be retrieved and shared automatically • Object-relational DBMS: Provides capabilities of both object-oriented and relational DBMS Object-Oriented Databases: THE DATABASE APPROACH TO DATA MANAGEMENT
28.
7.28 © 2006
by Prentice Hall • Conceptual design: Abstract model of database from a business perspective • Physical design: Detailed description of business information needs CREATING A DATABASE ENVIRONMENT Designing Databases:
29.
7.29 © 2006
by Prentice Hall • Entity-relationship diagram: Methodology for documenting databases illustrating relationships between database entities • Normalization: Process of creating small stable data structures from complex groups of data CREATING A DATABASE ENVIRONMENT Designing Databases: (Continued)
30.
7.30 © 2006
by Prentice Hall An Unnormalized Relation for ORDER CREATING A DATABASE ENVIRONMENT Figure 7-10
31.
7.31 © 2006
by Prentice Hall Normalized Tables Created from ORDER CREATING A DATABASE ENVIRONMENT Figure 7-11
32.
7.32 © 2006
by Prentice Hall An Entity-Relationship Diagram CREATING A DATABASE ENVIRONMENT Figure 7-12
33.
7.33 © 2006
by Prentice Hall Centralized database: • Used by single central processor or multiple processors in client/server network • There are advantages and disadvantages to having all corporate data in one location. • Security is higher in central environments, risks lower. • If data demands are highly decentralized, then a decentralized design is less costly, and more flexible. CREATING A DATABASE ENVIRONMENT Distributing Databases
34.
7.34 © 2006
by Prentice Hall • Databases can be decentralized either by partitioning or by replicating • Partitioned database: Database is divided into segments or regions. For example, a customer database can be divided into Eastern customers and Western customers, and two separate databases maintained in the two regions. CREATING A DATABASE ENVIRONMENT Distributed database:
35.
7.35 © 2006
by Prentice Hall • Duplicated database: The database is completely duplicated at two or more locations. The separate databases are synchronized in off hours on a batch basis. • Regardless of which method is chosen, data administrators and business managers need to understand how the data in different databases will be coordinated and how business processes might be effected by the decentralization. CREATING A DATABASE ENVIRONMENT
36.
7.36 © 2006
by Prentice Hall Distributed Databases CREATING A DATABASE ENVIRONMENT Figure 7-13
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7.37 © 2006
by Prentice Hall Ensuring Data Quality: • Corporate and government databases have unexpectedly poor levels of data quality. • National consumer credit reporting databases have error rates of 20-35%. • 32% of the records in the FBI’s Computerized Criminal History file are inaccurate, incomplete, or ambiguous. • Gartner Group estimates that consumer data in corporate databases degrades at the rate of 2% a month. CREATING A DATABASE ENVIRONMENT
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by Prentice Hall • The quality of decision making in a firm is directly related to the quality of data in its databases. • Data Quality Audit: Structured survey of the accuracy and level of completeness of the data in an information system • Data Cleansing: Consists of activities for detecting and correcting data in a database or file that are incorrect, incomplete, improperly formatted, or redundant CREATING A DATABASE ENVIRONMENT Ensuring Data Quality: (Continued)
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by Prentice Hall Online Analytical Processing (OLAP): • Multidimensional data analysis • Supports manipulation and analysis of large volumes of data from multiple dimensions/perspectives DATABASE TRENDS Multidimensional Data Analysis
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by Prentice Hall Multidimensional Data Model DATABASE TRENDS Figure 7-14
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by Prentice Hall Data warehouse: • Supports reporting and query tools • Stores current and historical data • Consolidates data for management analysis and decision making DATABASE TRENDS Data Warehousing and Data Mining
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by Prentice Hall Components of a Data Warehouse DATABASE TRENDS Figure 7-15
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by Prentice Hall Data mart: • Subset of data warehouse • Contains summarized or highly focused portion of data for a specified function or group of users DATABASE TRENDS Data mining: • Tools for analyzing large pools of data • Find hidden patterns and infer rules to predict trends
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by Prentice Hall Benefits of Data Warehouses: • Improved and easy accessibility to information • Ability to model and remodel the data DATABASE TRENDS
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by Prentice Hall The Web and Hypermedia database: • Organizes data as network of nodes • Links nodes in pattern specified by user • Supports text, graphic, sound, video, and executable programs DATABASE TRENDS Databases and the Web
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by Prentice Hall A Hypermedia Database DATABASE TRENDS Figure 7-16
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by Prentice Hall Database server: • Computer in a client/server environment runs a DBMS to process SQL statements and perform database management tasks. Application server: • Software handling all application operations DATABASE TRENDS Databases and the Web
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by Prentice Hall Linking Internal Databases to the Web DATABASE TRENDS Figure 7-17
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by Prentice Hall Management Opportunities: MANAGEMENT OPPORTUNITIES, CHALLENGES, AND SOLUTIONS Business firms have exceptional opportunities to exploit modern relational database technologies to improve decision making, and to increase the efficiency of their business processes.
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by Prentice Hall MANAGEMENT OPPORTUNITIES, CHALLENGES, AND SOLUTIONS Management Challenges: • Organizational obstacles to a database environment Need for cooperation in developing corporate-wide data administration • Cost/benefit considerations Bringing about significant change in the database environment of a firm can be very expensive and time consuming.
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by Prentice Hall Solution Guidelines: MANAGEMENT OPPORTUNITIES, CHALLENGES, AND SOLUTIONS The critical elements for creating a database environment are: • Data administration • Data-planning and modeling methodology • Database technology and management • Users
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by Prentice Hall Key Organizational Elements in the Database Environment MANAGEMENT OPPORTUNITIES, CHALLENGES, AND SOLUTIONS Figure 7-18
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