File Systems and Databases

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Chapter 1
File Systems and Databases
Database Systems Design, Implementation,
and Management, 4th Edition Peter Rob Carlos
Coronel
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Introducing the Database

• Major Database Concepts
• Data and information
• Data - Raw facts
• Information - Processed data
• Data management
• Database
• Metadata
• Database management system (DBMS)

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Sales per Employee for Each of ROBCORS Two
Divisions
Figure 1.1
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Introducing the Database

• Importance of DBMS
• It helps make data management more efficient and
  effective.
• Its query language allows quick answers to ad hoc
  queries.
• It provides end users better access to more and
  better-managed data.
• It promotes an integrated view of organizations
  operations -- big picture.
• It reduces the probability of inconsistent data.

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The DBMS Manages the Interaction Between the End
User and the Database
Figure 1.2
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Introducing the Database

• Why Database Design Is Important?
• A well-designed database facilitates data
  management and becomes a valuable information
  generator.
• A poorly designed database is a breeding ground
  for uncontrolled data redundancies.
• A poorly designed database generates errors that
  lead to bad decisions.

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Historical Roots

• Why Study File Systems?
• It provides historical perspective.
• It teaches lessons to avoid pitfalls of data
  management.
• Its simple characteristics facilitate
  understanding of the design complexity of a
  database.
• It provides useful knowledge for converting a
  file system to a database system.

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Contents of the CUSTOMER File
Figure 1.3
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Table 1.1 Basic File Terminology
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Contents of the AGENT File
Figure 1.4
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A Simple File System
Figure 1.5
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File System Critique

• File System Data Management
• File systems require extensive programming in a
  third-generation language (3GL).
• As the number of files expands, system
  administration becomes difficult.
• Making changes in existing file structures is
  important and difficult.
• Security features to safeguard data are difficult
  to program and usually omitted.
• Difficulty to pool data creates islands of
  information.

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File System Critique

• Structural and Data Dependence
• Structural Dependence
• A change in any files structure requires the
  modification of all programs using that file.
• Data Dependence
• A change in any files data characteristics
  requires changes in all data access programs.
• Significance of data dependence is the difference
  between the data logical format and the data
  physical format.
• Data dependence makes file systems extremely
  cumbersome from a programming and data management
  point of view.

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File System Critique

• Field Definitions and Naming Conventions
• A good (flexible) record definition anticipates
  reporting requirements by breaking up fields into
  their components.
• Example
• Customer Name ? Last Name, First Name, Initial
• Customer Address ? Street Address, City, State

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File System Critique

• Field Definitions and Naming Conventions
• Selecting proper field names is very important.
• Names must be as descriptive as possible within
  restrictions.
• Naming must reflect designers documentation
  needs and users reporting and processing
  requirements.

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File System Critique

• Data Redundancy
• Uncontrolled data redundancy sets the stage for
• Data Inconsistency (lack of data integrity)
• Data anomalies
• Modification anomalies
• Insertion anomalies
• Deletion anomalies

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Figure 1.6
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The Database System Environment
Figure 1.7
Figure 1.7
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Database Systems

• The Database System Components
• Hardware
• Computer
• Peripherals
• Software
• Operating systems software
• DBMS software
• Applications programs and utilities software

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Database Systems

• The Database System Components
• People
• Systems administrators
• Database administrators (DBAs)
• Database designers
• Systems analysts and programmers
• End users
• Procedures
• Instructions and rules that govern the design and
  use of the database system
• Data
• Collection of facts stored in the database

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Database Systems

• The Database System Components
• The complexity of database systems depends on
  various organizational factors
• Organizations size
• Organizations function
• Organizations corporate culture
• Organizational activities and environment
• Database solutions must be cost effective AND
  strategically effective.

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Database Systems

• Types of Database Systems
• Number of Users
• Single-user
• Desktop database
• Multiuser
• Workgroup database
• Enterprise database
• Scope
• Desktop
• Workgroup
• Enterprise

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Database Systems

• Types of Database Systems
• Location
• Centralized
• Distributed
• Use
• Transactional (Production)
• Decision support
• Data warehouse

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Database Systems

• DBMS Functions
• 1. Data Dictionary Management
• 2. Data Storage Management
• 3. Data Transformation and Presentation
• 4. Security Management
• 5. Multi-User Access Control
• 6. Backup and Recovery Management
• 7. Data Integrity Management
• 8. Database Access Languages (DDL and DML) and
  Application Programming Interfaces
• 9. Database Communication Interfaces

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Database Models

• A database model is a collection of logical
  constructs used to represent the data structure
  and the data relationships found within the
  database.
• Two Categories of Database Models
• Conceptual models focus on the logical nature of
  the data representation. They are concerned with
  what is represented rather than how it is
  represented.
• Implementation models place the emphasis on how
  the data are represented in the database or on
  how the data structures are implemented.

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Database Models

• Three Types of Relationships
• One-to-many relationships (1M)
• A painter paints many different paintings, but
  each one of them is painted by only that painter.
• PAINTER (1) paints PAINTING (M)
• Many-to-many relationships (MN)
• An employee might learn many job skills, and each
  job skill might be learned by many employees.
• EMPLOYEE (M) learns SKILL (N)
• One-to-one relationships (11)
• Each store is managed by a single employee and
  each store manager (employee) only manages a
  single store.
• EMPLOYEE (1) manages STORE (1)

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Database Models

• Three Types of Implementation Database Models
• Hierarchical database model
• Network database model
• Relational database model

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A Hierarchical Structure
Figure 1.8
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Database Models

• Hierarchical Database Model
• Basic Structure
• Collection of records logically organized to
  conform to the upside-down tree (hierarchical)
  structure.
• The top layer is perceived as the parent of the
  segment directly beneath it.
• The segments below other segments are the
  children of the segment above them.
• A tree structure is represented as a hierarchical
  path on the computers storage media.

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Database Models

• Hierarchical Database Model
• Advantages
• Conceptual simplicity
• Database security
• Data independence
• Database integrity
• Efficiency dealing with a large database
• Disadvantages
• Complex implementation
• Difficult to manage
• Lacks structural independence
• Applications programming and use complexity
• Implementation limitations
• Lack of standards

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Child with Multiple Parents
Figure 1.9
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Database Models

• Network Database Model
• Basic Structure
• Set -- A relationship is called a set. Each set
  is composed of at least two record types an
  owner (parent) record and a member (child)
  record.
• A set is represents a 1M relationship between
  the owner and the member.

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A Network Database Model
Figure 1.10
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Database Models

• Network Database Model
• Advantages
• Conceptual simplicity
• Handles more relationship types
• Data access flexibility
• Promotes database integrity
• Data independence
• Conformance to standards
• Disadvantages
• System complexity
• Lack of structural independence

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Database Models

• Relational Database Model
• Basic Structure
• RDBMS allows operations in a human logical
  environment.
• The relational database is perceived as a
  collection of tables.
• Each table consists of a series of row/column
  intersections.
• Tables (or relations) are related to each other
  by sharing a common entity characteristic.
• The relationship type is often shown in a
  relational schema.
• A table yields complete data and structural
  independence.

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Linking Relational Tables
Figure 1.11
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Database Models

• Relational Database Model
• Advantages
• Structural independence
• Improved conceptual simplicity
• Easier database design, implementation,
  management, and use
• Ad hoc query capability (SQL)
• Powerful database management system
• Disadvantages
• Substantial hardware and system software overhead
• Possibility of poor design and implementation
• Potential islands of information problems

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A Relational Schema
Figure 1.12
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Database Models

• Entity-Relationship Data Model
• It is one of the most widely accepted graphical
  data modeling tools.
• It graphically represents data as entities and
  their relationships in a database structure.
• It complements the relational data model concepts.

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Database Models

• Entity Relationship Data Model
• Basic Structure
• E-R models are normally represented in an entity
  relationship diagram (ERD).
• An entity is represented by a rectangle.
• Each entity is described by a set of attributes.
  An attribute describes a particular
  characteristics of the entity.
• A relationship is represented by a diamond
  connected to the related entities.

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Figure 1.13 Relationship Depiction The ERD
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Figure 1.14 Relationship Depiction The Crows
Foot
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Database Models

• Entity-Relationship Data Model
• Advantages
• Exceptional conceptual simplicity
• Visual representation
• Effective communication tool
• Integrated with the relational database model
• Disadvantages
• Limited constraint representation
• Limited relationship representation
• No data manipulation language
• Loss of information content

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Database Models

• Object-Oriented Database Model
• Characteristics
• An object is described by its factual content.
• An object includes information about
  relationships between the facts within the
  object, as well as with other objects.
• An object is a self-contained building block for
  autonomous structures.

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Database Models

• Object-Oriented Database Model
• Basic Structure
• Objects are abstractions of real-world entities
  or events.
• Attributes describe the properties of an object.
• Objects that share similar characteristics are
  grouped in classes.
• A class is a collection of similar objects with
  shared structure (attributes) and behavior
  (methods).
• Classes are organized in a class hierarchy.
• An object can inherit the attributes and methods
  of the classes above it.

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A Comparison The OO Data Model and the ER Model
Figure 1.15
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Database Models

• Object-Oriented Database Model
• Advantages
• Add semantic content
• Visual presentation includes semantic content
• Database integrity
• Both structural and data independence
• Disadvantages
• Lack of OODM standards
• Complex navigational data access
• Steep learning curve
• High system overhead slows transactions

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The Development of Data Models
Figure 1.16
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Wrap-Up The Evolution of Data Models

• Common characteristics required for data models
• A data model must show some degree of conceptual
  simplicity without compromising the semantic
  completeness.
• A data model must represent the real world as
  closely as possible.
• The representation of the real-world
  transformations (behavior) must be in compliance
  with the consistency and integrity
  characteristics of any data model.

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Wrap-Up The Evolution of Data Models

• Database Models and the Internet
• The use of the Internet as a prime business tool
  is shifting focus to database products that
  interface efficiently and easily with the
  Internet.
• Successful Internet age databases are
  characterized by
• Flexible, efficient, and secure Internet access.
• Support for complex data types and relationships.
• Seamless interfacing with multiple data sources
  and structures.
• Simplicity of the conceptual database model.
• An abundance of available database tools.
• A powerful DBMS to help make the DBAs job easier.