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DATABASES AND
DATABASE USERS
CHAPTER 1
1
Acknowledgement:
Most slides for this course have been adapted
from slides made available by Addison Wesley to
accompany Elmasri and Navathe’s textbook.
LECTURE OUTLINE
 Introduction
 An Example
 Characteristics of the Database Approach
 Actors on the Scene
 Workers behind the Scene
 When Not to Use a DBMS
2
WEALTH OF DATA
 Traditional database applications
• Store numeric short textual information
• Typically for managing enterprises
 Text and multimedia databases
• Store documents, digital images, audio, and video streams
 Geographic information systems (GIS)
• Store maps, weather data, and satellite images
• For route-finding, agriculture, and natural resource management
 Data warehouses and online analytical processing (OLAP) systems
• Store historical business information
• For business analytics and decision support
 Real-time and active database technology
• Store process models, constraints, and key performance indicators
• Control industrial and manufacturing processes
3
TERMINOLOGY
 Database
• Collection of related data (logically coherent)
• Known facts that can be recorded and that have implicit meaning
• Represents some aspect(s) of the real world (miniworld)
• Built for a specific purpose
 Examples of large databases
• Amazon.com, Canadian Census, The Bay’s product inventory, data
collection underlying Quest
4
TERMINOLOGY (CONT'D.)
 Database management system (DBMS)
• Collection of programs
• Enables users to create and maintain a database
• Allows multiple users and programs to access and manipulate the
database concurrently
• Provides protection against unauthorized access and manipulation
• Provides means to evolve database and program behaviour as
requirements change over time
 Examples of database management systems
• IBM’s DB2, Microsoft’s Access and SQL Server, Oracle, MySQL,
SAP’s SQL Anywhere
5
TERMINOLOGY (CONT'D.)
 Defining a database
• Specifying the data types, structures, and constraints of the data to
be stored
• Uses a Data Definition Language
 Meta-data
• Database definition or descriptive information
• Stored by the DBMS in the form of a database catalog or data
dictionary
 Phases for designing a database:
• Requirements specification and analysis
• Conceptual design
• e.g., using the Entity-Relationship model
• Logical design
• e.g., using the relational model
• Physical design
6
TERMINOLOGY (CONT'D.)
 Populating a database
• Inserting data to reflect the miniworld
 Query
• Interaction causing some data to be retrieved
• uses a Query Language
 Manipulating a database
• Querying and updating the database to understand/reflect miniworld
• Generating reports
• Uses a Data Manipulation Language
 Application program
• Accesses database by sending queries and updates to DBMS
• Transaction
• An atomic unit of queries and updates that must be executed as a
whole
• e.g., buying a product, transferring funds, switching co-op streams
7
DBMS SCHEMATIC
8
AN EXAMPLE
 Movie database
• Information concerning movies, actors, awards
 Data records
• Film
• Person
• Role
• Honours
 Define structure of each type of record by specifying data elements
to include and data type for each element
• String (sequence of alphabetic characters)
• Numeric (integer or real)
• Date (year or year-month-day)
• Monetary amount
• etc.
9
AN EXAMPLE (CONT'D.)
 Populate MOVIES database
• Store data to represent each film, actor, director, award, role
10
Film
title genre year director runtime budget gross
The Company
Men drama 2010 John Wells 104 15,000,000 4,439,063
Lincoln biography 2012 Steven Spielberg 150 65,000,000 181,408,467
War Horse drama 2011 Steven Spielberg 146 66,000,000 79,883,359
Argo drama 2012 Ben Affleck 120 44,500,000 135,178,251
Fire Sale comedy 1977 Alan Arkin 88 1,500,000 0
Person
name birth city
Ben Affleck 1972 Berkeley
Alan Arkin 1934 New York
Tommy Lee Jones 1946 San Saba
John Wells 1957 Alexandria
Steven Spielberg 1946 Cincinnati
Daniel Day-Lewis 1957 Greenwich
Role
actor movie persona
Ben Affleck Argo Tony Mendez
Alan Arkin Argo Lester Siegel
Ben Affleck The Company Men Bobby Walker
Tommy Lee Jones The Company Men Gene McClary
Tommy Lee Jones Lincoln Thaddeus Stevens
Alan Arkin Fire Sale Ezra Fikus
Daniel Day-Lewis Lincoln Abraham Lincoln
Honours
movie award category winner
Lincoln Critic's Choice actor Daniel Day-Lewis
Argo Critic's Choice director Ben Affleck
Lincoln Screen Actors Guild supporting actor Tommy Lee Jones
Lincoln Screen Actors Guild actor Daniel Day-Lewis
Lincoln Critic's Choice screenplay Tony Kushner
Argo Screen Actors Guild cast Argo
War Horse BMI Flim music John Williams
AN EXAMPLE (CONT'D.)
 Manipulation involves querying and updating
 Examples of queries:
• List the cast of characters for Lincoln.
• Who directed a drama in 2012?
• Who directed a film in which he or she also played a role?
• What awards were won by War Horse?
 Examples of updates:
• Record that Argo won a Golden Globe award for best picture.
• Add another $395,533 to the gross earnings for Lincoln.
• Change the birthplace for Daniel Day-Lewis to London.
• Delete Fire Sale from the database.
11
TERMINOLOGY (CONT'D.)
 Reorganizing a database
• Changes the metadata rather than the data
• More drastic than data updates
• May require massive changes to the data
• May require changes to some application programs
• Uses the Data Definition Language again
 Examples:
• Rename gross to be domestic earnings and add a new column for
foreign earnings.
• Move director from FILM to a separate relation DIRECTOR with
columns for person and movie
• Change birth from yyyy to yyyy/mm/dd
• Split name in PERSON to separate surname from given names.
• Include column movieID in FILM (to accommodate remakes and
other duplications of film title) and update other relations
accordingly.
12
PRE-DBMS DATABASES
 Used traditional file processing
• Each user defines and implements the files needed for a specific
software application
• As the application base grows
• many shared files
• a multitude of file structures
• a need to exchange data among applications
 Eventually recognized that data is a critical corporate asset (along
with capital and personnel)
13
DATABASE APPROACH
 Single repository maintains data that is defined once and then
accessed by various users
 Addresses a variety of problems
• redundancy: multiple copies
• inconsistency: independent updates
• inaccuracy: concurrent updates
• incompatibility: multiple formats
• insecurity: proliferation
• inauditability: poor chain of responsibility
• inflexibility: changes are difficult to apply
14
CHARACTERISTICS OF THE
DATABASE APPROACH
 Programs isolated from data through abstraction
• Does not expose details of how (or where) data is stored or how
operations are implemented
• Data sharing through multiple views
 Multiuser transaction processing
• Encapsulates sequence of operations to behave atomically
 Data is self-defining
• Database system contains complete definition of structure and
constraints as meta-data
• Database catalog used by:
• DBMS software
• Database users who need information about database structure
15
DATABASE CATALOG
16
ACTORS ON THE SCENE
 Database administrator (DBA) responsible for:
• Authorizing access to the database
• Coordinating and monitoring its use
• Acquiring software and hardware resources
• Tuning the DBMS for best performance
 Database designer responsible for:
• Identifying the data to be stored
• Choosing appropriate structures to represent and store this data
17
ACTORS ON THE SCENE (CONT'D.)
 End users
• Those whose jobs require access to the database
• Naive or parametric end users
• canned queries and updates
• Casual end users
• occasional, special-purpose access
• Sophisticated end users
• deep knowledge of database design and DBMS facilities
• Standalone users
• users of personal databases
 System analysts
• Determine requirements of end users
 Application programmers
• Implement complex specifications (business logic) as programs
18
WORKERS BEHIND THE SCENE
 DBMS system designers and implementers
• Design and implement the DBMS modules and interfaces as a
software package
 Tool developers
• Design and implement tools
 Operators and maintenance personnel
• Responsible for running and maintenance of hardware and
software environment for database system
19
WHEN NOT TO USE A DBMS
 More desirable to use regular files for:
• Simple, well-defined applications with no expected changes at all
• Small variety of data and/or small amount of data
• Stringent, real-time requirements that cannot afford DBMS
overhead
• Only single (personal) access to data
 Unlikely that any of these apply to corporate data management.
• In fact, corporations often maintain many databases across many
database systems.
20
LECTURE SUMMARY
 Database
• Collection of related data (recorded facts)
 DBMS
• Generalized software package for implementing and maintaining a
computerized database
• Provides many services to manage data resources
 Several categories of database users
21

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dbms-u1-1.pdf

  • 1. DATABASES AND DATABASE USERS CHAPTER 1 1 Acknowledgement: Most slides for this course have been adapted from slides made available by Addison Wesley to accompany Elmasri and Navathe’s textbook.
  • 2. LECTURE OUTLINE  Introduction  An Example  Characteristics of the Database Approach  Actors on the Scene  Workers behind the Scene  When Not to Use a DBMS 2
  • 3. WEALTH OF DATA  Traditional database applications • Store numeric short textual information • Typically for managing enterprises  Text and multimedia databases • Store documents, digital images, audio, and video streams  Geographic information systems (GIS) • Store maps, weather data, and satellite images • For route-finding, agriculture, and natural resource management  Data warehouses and online analytical processing (OLAP) systems • Store historical business information • For business analytics and decision support  Real-time and active database technology • Store process models, constraints, and key performance indicators • Control industrial and manufacturing processes 3
  • 4. TERMINOLOGY  Database • Collection of related data (logically coherent) • Known facts that can be recorded and that have implicit meaning • Represents some aspect(s) of the real world (miniworld) • Built for a specific purpose  Examples of large databases • Amazon.com, Canadian Census, The Bay’s product inventory, data collection underlying Quest 4
  • 5. TERMINOLOGY (CONT'D.)  Database management system (DBMS) • Collection of programs • Enables users to create and maintain a database • Allows multiple users and programs to access and manipulate the database concurrently • Provides protection against unauthorized access and manipulation • Provides means to evolve database and program behaviour as requirements change over time  Examples of database management systems • IBM’s DB2, Microsoft’s Access and SQL Server, Oracle, MySQL, SAP’s SQL Anywhere 5
  • 6. TERMINOLOGY (CONT'D.)  Defining a database • Specifying the data types, structures, and constraints of the data to be stored • Uses a Data Definition Language  Meta-data • Database definition or descriptive information • Stored by the DBMS in the form of a database catalog or data dictionary  Phases for designing a database: • Requirements specification and analysis • Conceptual design • e.g., using the Entity-Relationship model • Logical design • e.g., using the relational model • Physical design 6
  • 7. TERMINOLOGY (CONT'D.)  Populating a database • Inserting data to reflect the miniworld  Query • Interaction causing some data to be retrieved • uses a Query Language  Manipulating a database • Querying and updating the database to understand/reflect miniworld • Generating reports • Uses a Data Manipulation Language  Application program • Accesses database by sending queries and updates to DBMS • Transaction • An atomic unit of queries and updates that must be executed as a whole • e.g., buying a product, transferring funds, switching co-op streams 7
  • 9. AN EXAMPLE  Movie database • Information concerning movies, actors, awards  Data records • Film • Person • Role • Honours  Define structure of each type of record by specifying data elements to include and data type for each element • String (sequence of alphabetic characters) • Numeric (integer or real) • Date (year or year-month-day) • Monetary amount • etc. 9
  • 10. AN EXAMPLE (CONT'D.)  Populate MOVIES database • Store data to represent each film, actor, director, award, role 10 Film title genre year director runtime budget gross The Company Men drama 2010 John Wells 104 15,000,000 4,439,063 Lincoln biography 2012 Steven Spielberg 150 65,000,000 181,408,467 War Horse drama 2011 Steven Spielberg 146 66,000,000 79,883,359 Argo drama 2012 Ben Affleck 120 44,500,000 135,178,251 Fire Sale comedy 1977 Alan Arkin 88 1,500,000 0 Person name birth city Ben Affleck 1972 Berkeley Alan Arkin 1934 New York Tommy Lee Jones 1946 San Saba John Wells 1957 Alexandria Steven Spielberg 1946 Cincinnati Daniel Day-Lewis 1957 Greenwich Role actor movie persona Ben Affleck Argo Tony Mendez Alan Arkin Argo Lester Siegel Ben Affleck The Company Men Bobby Walker Tommy Lee Jones The Company Men Gene McClary Tommy Lee Jones Lincoln Thaddeus Stevens Alan Arkin Fire Sale Ezra Fikus Daniel Day-Lewis Lincoln Abraham Lincoln Honours movie award category winner Lincoln Critic's Choice actor Daniel Day-Lewis Argo Critic's Choice director Ben Affleck Lincoln Screen Actors Guild supporting actor Tommy Lee Jones Lincoln Screen Actors Guild actor Daniel Day-Lewis Lincoln Critic's Choice screenplay Tony Kushner Argo Screen Actors Guild cast Argo War Horse BMI Flim music John Williams
  • 11. AN EXAMPLE (CONT'D.)  Manipulation involves querying and updating  Examples of queries: • List the cast of characters for Lincoln. • Who directed a drama in 2012? • Who directed a film in which he or she also played a role? • What awards were won by War Horse?  Examples of updates: • Record that Argo won a Golden Globe award for best picture. • Add another $395,533 to the gross earnings for Lincoln. • Change the birthplace for Daniel Day-Lewis to London. • Delete Fire Sale from the database. 11
  • 12. TERMINOLOGY (CONT'D.)  Reorganizing a database • Changes the metadata rather than the data • More drastic than data updates • May require massive changes to the data • May require changes to some application programs • Uses the Data Definition Language again  Examples: • Rename gross to be domestic earnings and add a new column for foreign earnings. • Move director from FILM to a separate relation DIRECTOR with columns for person and movie • Change birth from yyyy to yyyy/mm/dd • Split name in PERSON to separate surname from given names. • Include column movieID in FILM (to accommodate remakes and other duplications of film title) and update other relations accordingly. 12
  • 13. PRE-DBMS DATABASES  Used traditional file processing • Each user defines and implements the files needed for a specific software application • As the application base grows • many shared files • a multitude of file structures • a need to exchange data among applications  Eventually recognized that data is a critical corporate asset (along with capital and personnel) 13
  • 14. DATABASE APPROACH  Single repository maintains data that is defined once and then accessed by various users  Addresses a variety of problems • redundancy: multiple copies • inconsistency: independent updates • inaccuracy: concurrent updates • incompatibility: multiple formats • insecurity: proliferation • inauditability: poor chain of responsibility • inflexibility: changes are difficult to apply 14
  • 15. CHARACTERISTICS OF THE DATABASE APPROACH  Programs isolated from data through abstraction • Does not expose details of how (or where) data is stored or how operations are implemented • Data sharing through multiple views  Multiuser transaction processing • Encapsulates sequence of operations to behave atomically  Data is self-defining • Database system contains complete definition of structure and constraints as meta-data • Database catalog used by: • DBMS software • Database users who need information about database structure 15
  • 17. ACTORS ON THE SCENE  Database administrator (DBA) responsible for: • Authorizing access to the database • Coordinating and monitoring its use • Acquiring software and hardware resources • Tuning the DBMS for best performance  Database designer responsible for: • Identifying the data to be stored • Choosing appropriate structures to represent and store this data 17
  • 18. ACTORS ON THE SCENE (CONT'D.)  End users • Those whose jobs require access to the database • Naive or parametric end users • canned queries and updates • Casual end users • occasional, special-purpose access • Sophisticated end users • deep knowledge of database design and DBMS facilities • Standalone users • users of personal databases  System analysts • Determine requirements of end users  Application programmers • Implement complex specifications (business logic) as programs 18
  • 19. WORKERS BEHIND THE SCENE  DBMS system designers and implementers • Design and implement the DBMS modules and interfaces as a software package  Tool developers • Design and implement tools  Operators and maintenance personnel • Responsible for running and maintenance of hardware and software environment for database system 19
  • 20. WHEN NOT TO USE A DBMS  More desirable to use regular files for: • Simple, well-defined applications with no expected changes at all • Small variety of data and/or small amount of data • Stringent, real-time requirements that cannot afford DBMS overhead • Only single (personal) access to data  Unlikely that any of these apply to corporate data management. • In fact, corporations often maintain many databases across many database systems. 20
  • 21. LECTURE SUMMARY  Database • Collection of related data (recorded facts)  DBMS • Generalized software package for implementing and maintaining a computerized database • Provides many services to manage data resources  Several categories of database users 21