1. DCT 2033 DATABASE MANAGEMENT SYSTEM Chapter 1
File Systems and Databases

2. Objective The difference between data and information
What a database is, about different types of databases,and why they are valuable assets for decision making.
Why database design is important
How modern database evolves from files and file systems
About flaws in file system data management
How a database system differs from a file system and how a DBMS functions within the database system.
Why data models are important
About the basic data-modeling building blocks
What business rules are and how they affect database design.
How the major data models evolved, and their advantages and disadvantages.
How data models can be classified by level of abstraction

3. Examples of Database Applications
Purchases from the supermarket
Purchases using your credit card
Booking a holiday at the travel agents
Using the local library
Taking out insurance
Renting a video
Using the Internet
Studying at university

4. Data vs. Information Data: Information:
Raw facts; building blocks of information
Unprocessed information
Information:
Data processed to reveal meaning
Accurate, relevant, and timely information is key to good decision making
Good decision making is the key to survival in a global environment

5. Transforming Raw Data into Information

6. Transforming Raw Data into Information (continued)

7. Transforming Raw Data into Information (continued)

8. Transforming Raw Data into Information (continued)

9. Introducing the Database and the DBMS
Database—shared, integrated computer structure that stores:
End user data (raw facts)
Metadata (data about data)

10. Introducing the Database and the DBMS (continued)
DBMS (database management system):
Collection of programs that manages database structure and controls access to data
Possible to share data among multiple applications or users
Makes data management more efficient and effective

11. 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 organization’s operations -- “big picture.”
It reduces the probability of inconsistent data.
End users have better access to more and better-managed data
Promotes integrated view of organization’s operations
Probability of data inconsistency is greatly reduced
Possible to produce quick answers to ad hoc queries

12. The DBMS Manages the Interaction Between the End User and the Database

13. Database Systems 4 Types of Database Systems: 3) Location Centralized
Distributed
4) Use
Transactional (Production)
Decision support
Data warehouse
4 Types of Database Systems:
1) Number of Users
Single-user
Desktop database
Multiuser
Workgroup database
Enterprise database
2) Scope
Desktop
Workgroup
Enterprise

14. Types of Databases Single-user: Desktop: Multi-user:
Supports only one user at a time
Desktop:
Single-user database running on a personal computer
Multi-user:
Supports multiple users at the same time

15. Types of Databases (continued)
Workgroup:
Multi-user database that supports a small group of users or a single department
Enterprise:
Multi-user database that supports a large group of users or an entire organization

16. Types of Databases (continued)
Can be classified by location:
Centralized:
Supports data located at a single site
Distributed:
Supports data distributed across several sites

17. Types of Databases (continued)
Can be classified by use:
Transactional (or production):
Supports a company’s day-to-day operations
Data warehouse:
Stores data used to generate information required to make tactical or strategic decisions
Often used to store historical data
Structure is quite different

18. Why Database Design is Important
Defines the database’s expected use
Different approach needed for different types of databases
Avoid redundant data
A well-designed database facilitates data management and becomes a valuable information generator.
Poorly designed database generates errors  leads to bad decisions  can lead to failure of organization

19. Historical Roots: Files and File Systems
Manual File systems:
Collection of file folders kept in file cabinet
Organization within folders based on data’s expected use (ideally logically related)
System adequate for small amounts of data with few reporting requirements
Finding and using data in growing collections of file folders became time-consuming and cumbersome
Collection of application programs that perform services for the end users (e.g. reports).
Each program defines and manages its own data.

20. Limitations of File-Based Approach
Separation and isolation of data
Each program maintains its own set of data.
Users of one program may be unaware of potentially useful data held by other programs.
Duplication of data
Same data is held by different programs.
Wasted space and potentially different values and/or different formats for the same item.

21. Limitations of File-Based Approach
Time-consuming, high-level activity
As number of files expands, system administration becomes difficult
Making changes in existing file structure is difficult
File structure changes require modifications in all programs that use data in that file

22. Limitations of File-Based Approach
Modifications are likely to produce errors, requiring additional time to “debug” the program
Security features hard to program and therefore often omitted
Data dependence
Incompatibility of files

23. Files and File Systems

24. Database Systems
Problems inherent in file systems make using a database system desirable
File system
Many separate and unrelated files
Database
Logically related data stored in a single logical data repository

25. Database Systems

26. Database System

27. Basic File Terminology

28. The Database System Environment
Database system is composed of 5 main parts:
Hardware
Computer
Peripherals
Software
Operating system software
DBMS software
Application programs and utility software
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

30. Database Systems
The complexity of database systems depends on various organizational factors:
Organization’s size
Organization’s function
Organization’s corporate culture
Organizational activities and environment
Database solutions must be cost effective AND strategically effective.

31. DBMS Functions
DBMS performs functions that guarantee integrity and consistency of data :
Data dictionary management
defines data elements and their relationships
any changes made in a database structure are automatically recorded in the data dictionary.
Data storage management
stores data and related data entry forms, report definitions, data validation rules, procedural code etc.

32. DBMS Functions (continued)
Data transformation and presentation
translates logical requests into commands to physically locate and retrieve the requested data
Security management
enforces user security and data privacy within database

33. DBMS Functions (continued)
5. Multiuser access control
uses sophisticated algorithms to ensure multiple users can access the database concurrently without compromising the integrity of the database
6. Backup and recovery management
provides backup and data recovery procedures
7. Data integrity management
promotes and enforces integrity rules

34. DBMS Functions (continued)
8. Database access languages and application programming interfaces
provide data access through a query language
DBMS query languages contains 2 component: data definition languages & data manipulation languages
9. Database communication interfaces
allow database to accept end-user requests via multiple, different network environments

35. DBMS Functions (continued)

36. DBMS Functions (continued)

37. Advantages of DBMS Control of the redundancy Data consistency
Sharing of data
Improved data intergrity
Improved security
Enforcement of standard
More information from the same amount of data
Economy scale

38. Advantages of DBMS Balance of conflicting requirements
Improved data accessibility and sponsiveness
Increase productivity
Improved backup and recovery services

39. Disadvantages of DBMS Complexity, size Cost of DBMS
Additional hardware costs
Cost of conversion
Performance
Higher impact of a failure

40. Summary
Data are raw facts. Information is the result of processing data to reveal its meaning.
To implement and manage a database, use a DBMS.
Database design defines the database structure.
A well-designed database facilitates data management and generates accurate and valuable information.
A poorly designed database can lead to bad decision making, and bad decision making can lead to the failure of an organization.

41. Summary (continued) Databases were preceded by file systems.
Limitations of file system data management:
requires extensive programming
system administration complex and difficult
making changes to existing structures is difficult
security features are likely to be inadequate
independent files tend to contain redundant data
DBMS’s were developed to address file systems’ inherent weaknesses

42. Data Models
Definition: is the relatively simple representation, usually graphical, of real-world data structures.
Function: understand the complexities of the real-world environment.
Two components of data models:
1) Structure
- refers to the way the system structure data or, the way the users feel the data is structured.
2) Operation
- facilities given to the user of the DBMS to manipulate data within the database.

43. Data Model Basic Building Blocks
Basic building blocks of data model:entity, attributes, relationship
Entity is anything about which data are to be collected and stored(person, places, things, or event for which data is collected)
Attribute is a characteristic/ property of an entity
Relationship describes an association among (two or more) entities
One-to-many (1:M) relationship
Many-to-many (M:N or M:M) relationship
One-to-one (1:1) relationship

44. Data Model Basic Building Blocks
Three Types of Relationships:
One-to-many relationships (1:M)
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 (M:N)
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 (1:1)
Each store is managed by a single employee and each store manager (employee) only manages a single store.
EMPLOYEE (1) manages STORE (1)

45. The Evolution of Data Models
FOUR models/ categories of Implementation Data Models
Hierarchical
Network
Relational
Object oriented

47. Hierarchical 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 computer’s storage media.

48. The Hierarchical Model
Characteristics
Basic concepts form the basis for subsequent database development
Limitations lead to a different way of looking at database design
Basic concepts show up in current data models
Best understood by examining manufacturing process

49. The Hierarchical Model
Advantages
Conceptual simplicity
Database security
Data independence
Database integrity
Efficiency dealing with a large database

50. The Hierarchical Model
Disadvantages
Complex implementation
Difficult to manage
Lacks structural independence
Applications programming and use complexity
Implementation limitations
Lack of standards

51. Network Database Models
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 1:M relationship between the owner and the member.

53. The Network Data 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

54. Relational Database Models
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.

56. Advantages
Structural independence
Improved conceptual simplicity
Easier database design, implementation, management & 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

57. Entity-Relationship Data Models
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.

58. Basic Structure of ER Model
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.

61. Advantages of the ER model
Exceptional conceptual simplicity
Visual representation
Effective communication tool
Integrated with the relational database model
Disadvantages of the ER model
Limited constraint representation
Limited relationship representation
No data manipulation language
Loss of information content

62. Data Redundancy Data redundancy results in data inconsistency
Different and conflicting versions of the same data appear in different places
Errors more likely to occur when complex entries are made in several different files and/or recur frequently in one or more files
Data anomalies develop when required changes in redundant data are not made successfully

63. Data Redundancy Types of data anomalies: Update anomalies
Occur when changes must be made to existing records
Insertion anomalies
Occur when entering new records
Deletion anomalies
Occur when deleting records

64. Advantages of Database Processing
Economy pf scale
Getting more information from same amount of data
Sharing of data
Balancing conflicting requirements
Enforcement of standards
Controlled redundancy
Consistency
Integrity
Security
Flexibility and responsiveness
Increased programmer productivity
Improved program maintenance
Data independence

65. Disadvantages of Database Processing
Size
Complexity
Cost of DBMSs
Additional hardware requirements
Higher impact of a failure
Recovery more difficult

66. Recap…. Data, information, metadata, database, DBMS DBMS function.
Entities, attributes, relationship
Files, records, fields
Data models(relational model, network model, hierarchical model, object-oriented model)
Advantages and disadvantages of database processing