File Systems and Databases

1. Chapter 1 File Systems and Databases Database Systems: Design, Implementation, and Management, 4th Edition Peter Rob & Carlos Coronel

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

3. Sales per Employee for Each of ROBCOR’S Two Divisions Figure 1.1

4. 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 organization’s operations -- “big picture.” • It reduces the probability of inconsistent data.

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

6. 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.

7. 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.

8. Contents of the CUSTOMER File Figure 1.3

9. Table 1.1 Basic File Terminology

10. Contents of the AGENT File Figure 1.4

11. A Simple File System Figure 1.5

12. 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.

13. File System Critique • Structural and Data Dependence • Structural Dependence A change in any file’s structure requires the modification of all programs using that file. • Data Dependence A change in any file’s 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.

14. 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

15. 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 designer’s documentation needs and user’s reporting and processing requirements.

16. 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

17. Figure 1.6

18. The Database System Environment Figure 1.7 Figure 1.7

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

20. 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

21. Database Systems • The Database System Components • 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.

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

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

24. 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

25. 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.

26. Database Models • 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)

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

28. A Hierarchical Structure Figure 1.8

29. 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 computer’s storage media.

30. 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

31. Child with Multiple Parents Figure 1.9

32. 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 1:M relationship between the owner and the member.

33. A Network Database Model Figure 1.10

34. 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

35. 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.

36. Linking Relational Tables Figure 1.11

37. 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

38. A Relational Schema Figure 1.12

39. 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.

40. 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.

41. Figure 1.13 Relationship Depiction: The ERD

42. Figure 1.14 Relationship Depiction: The Crow’s Foot

43. 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

44. 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.

45. Database Models • Object-Oriented Database Model • Basic Structure • Objectsare 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.

46. A Comparison: The OO Data Model and the ER Model Figure 1.15

47. 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

48. The Development of Data Models Figure 1.16

49. 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.

50. 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 DBA’s job easier.