This document discusses database management systems and how they organize information. It compares traditional file organization techniques to database management. It describes the different components of a database management system including the data definition language, data manipulation language, and data dictionary. It also discusses different database models like relational, hierarchical, and network models. Finally, it outlines the process for creating a database including conceptual and physical design.

1. 7 MANAGING DATA RESOURCES c h a p t e r

2. LEARNING OBJECTIVES COMPARE TRADITIONAL FILE ORGANIZATION & MANAGEMENT TECHNIQUES DESCRIBE HOW DATABASE MANAGEMENT SYSTEM ORGANIZES INFORMATION *

3. LEARNING OBJECTIVES IDENTIFY TYPES OF DATABASE, PRINCIPLES OF DATABASE DESIGN DISCUSS DATABASE TRENDS *

4. MANAGEMENT CHALLENGES TRADITIONAL DATA FILE ENVIRONMENT DATABASE APPROACH TO DATA MANAGEMENT CREATING DATABASE ENVIRONMENT DATABASE TRENDS *

5. MANAGEMENT CHALLENGES 1. ORGANIZATIONAL OBSTACLES: Challenges existing power structure, requires organizational restructure 2. COST / BENEFIT CONSIDERATIONS: Large initial costs, delayed benefits, tangible, intangible *

6. FILE ORGANIZATION BIT: Binary Digit (0,1; Y,N; On,Off) BYTE: Combination of BITS which represent a CHARACTER FIELD: Collection of BYTES which represent a DATUM or Fact RECORD: Collection of FIELDS which reflect a TRANSACTION *

7. FILE ORGANIZATION FILE: A Collection of similar RECORDS DATABASE: An Organization’s Electronic Library of FILES organized to serve business applications *

8. FILE ORGANIZATION ENTITY: Person, place, thing, event about which data must be kept ATTRIBUTE: Description of a particular ENTITY KEY FIELD: Field used to retrieve, update, sort RECORD *

9. KEY FIELD Field in Each Record Uniquely Identifies THIS Record For RETRIEVAL UPDATING SORTING *

10. DATA REDUNDANCY PROGRAM / DATA DEPENDENCY LACK OF FLEXIBILITY POOR SECURITY LACK OF DATA SHARING & AVAILABILITY * PROBLEMS WITH TRADITIONAL FILE ENVIRONMENT Flat File

11. SEQUENTIAL VS. DIRECT FILE ORGANIZATION SEQUENTIAL: Tape oriented; one file follows another; follows physical sequence DIRECT: Disk oriented; can be accessed without regard to physical sequence *

12. FILING METHODS INDEXED SEQUENTIAL ACCESS METHOD (ISAM) : EACH RECORD IDENTIFIED BY KEY GROUPED IN BLOCKS AND CYLINDERS KEYS IN INDEX VIRTUAL STORAGE ACCESS METHOD (VSAM) : MEMORY DIVIDED INTO AREAS & INTERVALS DYNAMIC FILE SPACE VSAM WIDELY USED FOR RELATIONAL DATABASES DIRECT FILE ACCESS METHOD *

13. DIRECT FILE ACCESS METHOD EACH RECORD HAS KEY FIELD KEY FIELD FED INTO TRANSFORM ALGORITHM ALGORITHM GENERATES PHYSICAL STORAGE LOCATION OF RECORD (RECORD ADDRESS) *

14. DATABASE MANAGEMENT SYSTEM (DBMS) SOFTWARE TO CREATE & MAINTAIN DATA ENABLES BUSINESS APPLICATIONS TO EXTRACT DATA INDEPENDENT OF SPECIFIC COMPUTER PROGRAMS * DBMS

15. COMPONENTS OF DBMS: DATA DEFINITION LANGUAGE: Defines data elements in database DATA MANIPULATION LANGUAGE: Manipulates data for applications DATA DICTIONARY: Formal definitions of all variables in database, controls variety of database contents, data elements * DBMS

16. STRUCTURED QUERY LANGUAGE (SQL) EMERGING STANDARD DATA MANIPULATION LANGUAGE FOR RELATIONAL DATABASES * DBMS

17. ELEMENTS OF SQL SELECT: List of columns from tables desired FROM: Identifies tables from which columns will be selected WHERE: Includes conditions for selecting specific rows, conditions for joining multiple tables * DBMS

18. TWO VIEWS OF DATA PHYSICAL VIEW: Where is data physically? DRIVE, DISK, SURFACE, TRACK, SECTOR (BLOCK), RECORD TAPE, BLOCK, RECORD NUMBER (KEY) LOGICAL VIEW: What data is needed by application? SUCCESSION OF FACTS NEEDED BY APPLICATION NAME, TYPE, LENGTH OF FIELD * BIT BYTE FIELD RECORD FILE DATABASE DBMS

19. RELATIONAL DATA MODEL DATA IN TABLE FORMAT RELATION: TABLE TUPLE: ROW (RECORD) IN TABLE FIELD: COLUMN (ATTRIBUTE) IN TABLE *

20. TYPES OR RELATIONS ONE-TO-ONE: STUDENT ID ONE-TO-MANY: CLASS STUDENT A STUDENT B STUDENT C MANY-TO-MANY: STUDENT A STUDENT B STUDENT C CLASS 1 CLASS 2

21. HIERARCHICAL DATA MODEL ROOT FIRST CHILD 2nd CHILD Ratings Salary Compensation Job Assignments Pension Insurance Health Benefits Employer

22. NETWORK DATA MODEL VARIATION OF HIERARCHICAL MODEL USEFUL FOR MANY-TO-MANY RELATIONSHIPS * NETWORK A NETWORK B NETWORK C NETWORK 1 NETWORK 2

23. OTHER SYSTEMS LEGACY SYSTEM: older system OBJECT - ORIENTED DBMS: stores data & procedures as objects OBJECT - RELATIONAL DBMS: hybrid *

24. CREATING A DATABASE CONCEPTUAL DESIGN PHYSICAL DESIGN *

25. CREATING A DATABASE CONCEPTUAL DESIGN: ABSTRACT MODEL, BUSINESS PERSPECTIVE HOW WILL DATA BE GROUPED? RELATIONSHIPS AMONG ELEMENTS ESTABLISH END-USER NEEDS *

26. DETAILED MODEL BY DATABASE SPECIALISTS ENTITY-RELATIONSHIP DIAGRAM NORMALIZATION HARDWARE / SOFTWARE SPECIFIC * CREATING A DATABASE PHYSICAL DESIGN:

27. ELEMENTS OF DATABASE ENVIRONMENT DATABASE MANAGEMENT SYSTEM DATA ADMINISTRATION DATABASE TECHNOLOGY & MANAGEMENT USERS DATA PLANNING & MODELING METHODOLOGY

28. ENTITY- RELATIONSHIP DIAGRAM 1 1 M 1 ORDER CAN HAVE PART SUPPLIER CAN HAVE ORDER: #, DATE, PART #, QUANTITY PART: #, DESCRIPTION, UNIT PRICE, SUPPLIER # SUPPLIER: #, NAME, ADDRESS

29. NORMALIZATION PROCESS OF CREATING SMALL DATA STRUCTURES FROM COMPLEX GROUPS OF DATA EXAMPLES: ACCOUNTS RECEIVABLE PERSONNEL RECORDS PAYROLL *

30. DISTRIBUTED DATABASES PARTITIONED: remote CPUs (connected to host) have files unique to that site, e.g., records on local customers DUPLICATE: each remote CPU has copies of common files, e.g., layouts for standard reports and forms *

31. DATABASE ADMINISTRATION DEFINES & ORGANIZES DATABASE STRUCTURE AND CONTENT DEVELOPS SECURITY PROCEDURES DEVELOPS DATABASE DOCUMENTATION MAINTAINS DBMS *

32. DATABASE TRENDS MULTIDIMENSIONAL DATA ANALYSIS: 3D (or higher) groupings to store complex data HYPERMEDIA: Nodes contain text, graphics, sound, video, programs. organizes data as nodes. *

33. DATABASE TRENDS DATA WAREHOUSE: Organization’s electronic library stores consolidated current & historic data for management reporting & analysis ON-LINE ANALYTICAL PROCESSING (OLAP): Tools for multi- dimensional data analysis *

34. COMPONENTS OF DATA WAREHOUSE

35. DATABASE TRENDS DATA MART: Small data warehouse for special function, e.g., Focused marketing based on customer info DATAMINING: Tools for finding hidden patterns, relation- ships, for predicting trends *

36. DATABASE TRENDS LINKING DATABASES TO THE WEB: WEB USER CONNECTS TO VENDOR DATABASE SPECIAL SOFTWARE CONVERTS HTML TO SQL SQL FINDS DATA, SERVER CONVERTS RESULT TO HTML *

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