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8. MANAGING DATA RESOURCES. 8.1. LEARNING OBJECTIVES. COMPARE TRADITIONAL FILE ORGANIZATION & MANAGEMENT TECHNIQUES EXPLAIN PROBLEMS OF TRADITIONAL FILE ENVIRONMENT DESCRIBE HOW DATABASE MANAGEMENT SYSTEM ORGANIZES DATA *. 8.2. LEARNING OBJECTIVES.

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8.1

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  1. 8. MANAGING DATA RESOURCES 8.1

  2. LEARNING OBJECTIVES • COMPARE TRADITIONAL FILE ORGANIZATION & MANAGEMENT TECHNIQUES • EXPLAIN PROBLEMS OF TRADITIONAL FILE ENVIRONMENT • DESCRIBE HOW DATABASE MANAGEMENT SYSTEM ORGANIZES DATA * 8.2

  3. LEARNING OBJECTIVES • IDENTIFY 3 DATABASE MODELS, PRINCIPLES OF DATABASE DESIGN • DISCUSS DATABASE TRENDS • ANALYZE MANAGERIAL, ORGANIZATIONAL REQUIREMENTS FOR CREATING DATABASE ENVIRONMENT * 8.3

  4. MANAGEMENT CHALLENGES • TRADITIONAL DATA FILE ENVIRONMENT • DATABASE ENVIRONMENT • DESIGNING DATABASES • DATABASE TRENDS • MANAGEMENT REQUIREMENTS FOR DATABASE SYSTEMS * 8.4

  5. 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 * 8.5

  6. FILE ORGANIZATION • FILE:A Collection of Similar RECORDS • DATABASE:An Organization’s Electronic Library of FILES * 8.5

  7. 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 * 8.7

  8. KEY FIELD Field in Each Record Uniquely Identifies THIS Record For RETRIEVAL UPDATING SORTING * 8.8

  9. SEQUENTIAL VS. DIRECTFILE ORGANIZATION • SEQUENTIAL:Tape Oriented; One File Follows another; Follows Physical Sequence • DIRECT:Disk Oriented; Can be Accessed Without Regard to Physical Sequence * 8.9

  10. 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 RELATIONALDATABASES • DIRECT FILE ACCESS METHOD * 8.10

  11. DIRECT FILE ACCESS METHOD • EACH RECORD HAS KEY FIELD • KEY FIELD FED INTO TRANSFORM ALGORITHM • ALGORITHM GENERATES PHYSICAL STORAGE LOCATION OF RECORD (RECORD ADDRESS) * 8.11

  12. TRADITIONAL FILE ENVIRONMENT (FLAT FILE) • DATA REDUNDANCY • PROGRAM / DATA DEPENDENCY • LACK OF FLEXIBILITY • POOR SECURITY • LACK OF DATA SHARING & AVAILABILITY * 8.12

  13. DATABASE ORGANIZATION’S ELECTRONIC LIBRARY STORES & MANAGES DATA IN A CONVENIENT FORM * 8.13

  14. DATABASE MANAGEMENT SYSTEM (DBMS) SOFTWARE TO CREATE & MAINTAIN DATA ENABLES BUSINESS APPLICATIONS TO EXTRACT DATA INDEPENDENT OF SPECIFIC COMPUTER PROGRAMS * DBMS 8.14

  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 * DBMS 8.15

  16. STRUCTURED QUERY LANGUAGE (SQL) EMERGING STANDARD DATA MANIPULATION LANGUAGE FOR RELATIONAL DATABASES * DBMS 8.16

  17. 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 * DBMS 8.17 BIT BYTE FIELD RECORD FILE DATABASE

  18. ADVANTAGES OF DBMS: • REDUCES COMPLEXITY • REDUCES DATA REDUNDANCY / INCONSISTENCY • CENTRAL CONTROL OF DATA CREATION / DEFINITIONS • REDUCES PROGRAM / DATA DEPENDENCE * DBMS 8.18

  19. ADVANTAGES OF DBMS: • REDUCES DEVELOPMENT / MAINTENANCE COSTS • ENHANCES SYSTEM FLEXIBILITY • INCREASES ACCESS / AVAILABILITY OF INFORMATION * DBMS 8.19

  20. ROOT Employer Job Benefits Compensation FIRST CHILD Assignments 2nd CHILD Ratings Salary Pension Insurance Health HIERARCHICAL DATA MODEL 8.20

  21. RECORD 1 POINTER RECORD 2 POINTER RECORD 3 POINTER POINTER • FIELD IN ONE RECORD IS ADDRESS OF NEXT RECORD IN SEQUENCE * 8.21

  22. STUDENT ID ONE-TO-ONE: CLASS ONE-TO-MANY: STUDENT A STUDENT B STUDENT C CLASS 1 CLASS 2 MANY-TO-MANY: STUDENT A STUDENT B STUDENT C TYPES OR RELATIONS 8.22

  23. NETWORK 1 NETWORK 2 NETWORK A NETWORK B NETWORK C NETWORK DATA MODEL • VARIATION OF HIERARCHICAL MODEL • USEFUL FOR MANY-TO-MANY RELATIONSHIPS * 8.23

  24. RELATIONAL DATA MODEL • DATA IN TABLE FORMAT • RELATION: TABLE • TUPLE: ROW (RECORD) IN TABLE • FIELD: COLUMN (ATTRIBUTE) IN TABLE * 8.24

  25. COMPARISON OF DATABASE ALTERNATIVESHIERARCHICAL: PROCESSING EFFICIENCY:HIGH FLEXIBILITY:LOW USER FRIENDLY:LOW PROGRAM COMPLEXITY:HIGH * 8.25

  26. COMPARISON OF DATABASE ALTERNATIVESNETWORK: PROCESSING EFFICIENCY:MEDIUM / HIGH FLEXIBILITY:LOW / MEDIUM USER FRIENDLY:LOW / MODERATE PROGRAM COMPLEXITY:HIGH * 8.26

  27. COMPARISON OF DATABASE ALTERNATIVESRELATIONAL: PROCESSING EFFICIENCY:LOW BUT IMPROVING FLEXIBILITY:HIGH USER FRIENDLY:HIGH PROGRAM COMPLEXITY:LOW * 8.27

  28. CREATING A DATABASE • CONCEPTUAL DESIGN • PHYSICAL DESIGN * 8.28

  29. CREATING A DATABASECONCEPTUAL DESIGN: • ABSTRACT MODEL, BUSINESS PERSPECTIVE • HOW WILL DATA BE GROUPED? • RELATIONSHIPS AMONG ELEMENTS • ESTABLISH END-USER NEEDS * 8.29

  30. CREATING A DATABASEPHYSICAL DESIGN: • DETAILED MODEL BY DATABASE SPECIALISTS • ENTITY-RELATIONSHIP DIAGRAM • NORMALIZATION • HARDWARE / SOFTWARE SPECIFIC * 8.30

  31. ORDER ORDER: #, DATE, PART #, QUANTITY PART: #, DESCRIPTION, UNIT PRICE, SUPPLIER # SUPPLIER: #, NAME, ADDRESS 1 CAN HAVE 1 PART M CAN HAVE 1 SUPPLIER ENTITY- RELATIONSHIP DIAGRAM 8.31

  32. NORMALIZATION PROCESS OF CREATING SMALL DATA STRUCTURES FROM COMPLEX GROUPS OF DATA EXAMPLES: • ACCOUNTS RECEIVABLE • PERSONNEL RECORDS • PAYROLL * 8.32

  33. DATABASE TRENDS • DISTRIBUTED PROCESSING:Multiple Geographical / Functional Systems Connected with Network • DISTRIBUTED DATABASE:Data Physically Stored in more than one Location • PARTITIONED • DUPLICATE * 8.33

  34. 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 * 8.34

  35. DATABASE TRENDS • OBJECT- ORIENTED:Data and Procedures Stored Together; can be Retrieved, Shared • HYPERMEDIA:Nodes Contain Text, Graphics, Sound, Video, Programs. Organizes Data as Nodes. • MULTIDIMENSIONAL:3D (or higher) Groupings to Store Complex Data * 8.35

  36. DATABASE TRENDS • DATA WAREHOUSE:Organization’s Electronic Library Stores Consolidated Current & Historic Data for Management Reporting & Analysis • DATA MART:small data warehouse for special function, e.g., focused marketing based on customer info * 8.36

  37. COMPONENTS OF DATA WAREHOUSE 8.37

  38. DATABASE TRENDS • ON-LINE ANALYTICAL PROCESSING (OLAP):ability to manipulate, analyze large volumes of data from multiple perspectives • LINKING DATABASES TO THE WEB * 8.38

  39. DATA ADMINISTRATION DATABASE TECHNOLOGY & MANAGEMENT DATABASE MANAGEMENT SYSTEM DATA PLANNING & MODELING METHODOLOGY USERS ELEMENTS OF DATABASE ENVIRONMENT 8.39

  40. DATABASE ADMINISTRATION • DEFINES & ORGANIZES DATABASE STRUCTURE AND CONTENT • DEVELOPS SECURITY PROCEDURES • DEVELOPS DATABASE DOCUMENTATION • MAINTAINS DBMS * 8.40

  41. Connect to the INTERNET PRESS LEFT MOUSE BUTTON ON ICON TO CONNECT TO THE LAUDON & LAUDON WEB SITE FOR MORE INFORMATION ON THIS CHAPTER 8.41

  42. 8. MANAGING DATA RESOURCES 8.42

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