Download presentation
Presentation is loading. Please wait.
Published byBarnaby Waters Modified over 9 years ago
1
7.1 Prof Jess Role @ UEAB 2010 7 7 MANAGING DATA DATARESOURCES
2
7.2 Prof Jess Role @ UEAB 2010 LEARNING OBJECTIVES COMPARE TRADITIONAL FILE ORGANIZATION & MANAGEMENT TECHNIQUESCOMPARE TRADITIONAL FILE ORGANIZATION & MANAGEMENT TECHNIQUES DESCRIBE HOW DATABASE MANAGEMENT SYSTEM ORGANIZES INFORMATIONDESCRIBE HOW DATABASE MANAGEMENT SYSTEM ORGANIZES INFORMATION* © 2008 by Prentice Hall
3
7.3 Prof Jess Role @ UEAB 2010 LEARNING OBJECTIVES IDENTIFY TYPES OF DATABASE, PRINCIPLES OF DATABASE DESIGNIDENTIFY TYPES OF DATABASE, PRINCIPLES OF DATABASE DESIGN DISCUSS DATABASE TRENDSDISCUSS DATABASE TRENDS* © 2008 by Prentice Hall
4
7.4 Prof Jess Role @ UEAB 2010 MANAGEMENT CHALLENGES TRADITIONAL DATA FILE ENVIRONMENTTRADITIONAL DATA FILE ENVIRONMENT DATABASE APPROACH TO DATA MANAGEMENTDATABASE APPROACH TO DATA MANAGEMENT CREATING DATABASE ENVIRONMENTCREATING DATABASE ENVIRONMENT DATABASE TRENDSDATABASE TRENDS* TRADITIONAL DATA FILE ENVIRONMENTTRADITIONAL DATA FILE ENVIRONMENT DATABASE APPROACH TO DATA MANAGEMENTDATABASE APPROACH TO DATA MANAGEMENT CREATING DATABASE ENVIRONMENTCREATING DATABASE ENVIRONMENT DATABASE TRENDSDATABASE TRENDS*
5
7.5 Prof Jess Role @ UEAB 2010 MANAGEMENT CHALLENGES 1. ORGANIZATIONAL OBSTACLES: Challenges existing power structure, requires organizational restructure 2. COST / BENEFIT CONSIDERATIONS: Large initial costs, delayed benefits, tangible, intangible *
6
7.6 Prof Jess Role @ UEAB 2010 FILE ORGANIZATION BIT: Binary Digit (0,1; Y,N; On,Off)BIT: Binary Digit (0,1; Y,N; On,Off) BYTE: Combination of BITS which represent a CHARACTERBYTE: Combination of BITS which represent a CHARACTER FIELD: Collection of BYTES which represent a DATUM or FactFIELD: Collection of BYTES which represent a DATUM or Fact RECORD: Collection of FIELDS which reflect a TRANSACTIONRECORD: Collection of FIELDS which reflect a TRANSACTION*
7
7.7 Prof Jess Role @ UEAB 2010 FILE ORGANIZATION FILE: A Collection of similar RECORDSFILE: A Collection of similar RECORDS DATABASE: An Organization ’ s Electronic Library of FILES organized to serve business applicationsDATABASE: An Organization ’ s Electronic Library of FILES organized to serve business applications*
8
7.8 Prof Jess Role @ UEAB 2010 FILE ORGANIZATION ENTITY: Person, place, thing, event about which data must be keptENTITY: Person, place, thing, event about which data must be kept ATTRIBUTE: Description of a particular ENTITYATTRIBUTE: Description of a particular ENTITY KEY FIELD: Field used to retrieve, update, sort RECORDKEY FIELD: Field used to retrieve, update, sort RECORD*
9
7.9 Prof Jess Role @ UEAB 2010 KEY FIELD Field in Each Record Uniquely Identifies THIS Record For RETRIEVAL UPDATING UPDATINGSORTING*
10
7.10 Prof Jess Role @ UEAB 2010 DATA REDUNDANCYDATA REDUNDANCY PROGRAM / DATA DEPENDENCYPROGRAM / DATA DEPENDENCY LACK OF FLEXIBILITYLACK OF FLEXIBILITY POOR SECURITYPOOR SECURITY LACK OF DATA SHARING & AVAILABILITYLACK OF DATA SHARING & AVAILABILITY* PROBLEMS WITH TRADITIONAL FILE ENVIRONMENT Flat File
11
7.11 Prof Jess Role @ UEAB 2010 SEQUENTIAL VS. DIRECT FILE ORGANIZATION SEQUENTIAL: Tape oriented; one file follows another; follows physical sequenceSEQUENTIAL: Tape oriented; one file follows another; follows physical sequence DIRECT: Disk oriented; can be accessed without regard to physical sequenceDIRECT: Disk oriented; can be accessed without regard to physical sequence*
12
7.12 Prof Jess Role @ UEAB 2010 FILING METHODS INDEXED SEQUENTIAL ACCESS METHOD (ISAM) :INDEXED SEQUENTIAL ACCESS METHOD (ISAM) : –EACH RECORD IDENTIFIED BY KEY –GROUPED IN BLOCKS AND CYLINDERS –KEYS IN INDEX VIRTUAL STORAGE ACCESS METHOD (VSAM) :VIRTUAL STORAGE ACCESS METHOD (VSAM) : –MEMORY DIVIDED INTO AREAS & INTERVALS –DYNAMIC FILE SPACE VSAM WIDELY USED FOR RELATIONAL DATABASES VSAM WIDELY USED FOR RELATIONAL DATABASES DIRECT FILE ACCESS METHODDIRECT FILE ACCESS METHOD*
13
7.13 Prof Jess Role @ UEAB 2010 DIRECT FILE ACCESS METHOD EACH RECORD HAS KEY FIELDEACH RECORD HAS KEY FIELD KEY FIELD FED INTO TRANSFORM ALGORITHMKEY FIELD FED INTO TRANSFORM ALGORITHM ALGORITHM GENERATES PHYSICAL STORAGE LOCATION OF RECORD (RECORD ADDRESS)ALGORITHM GENERATES PHYSICAL STORAGE LOCATION OF RECORD (RECORD ADDRESS)*
14
7.14 Prof Jess Role @ UEAB 2010 DATABASE MANAGEMENT SYSTEM (DBMS) SOFTWARE TO CREATE & MAINTAIN DATA ENABLES BUSINESS APPLICATIONS TO EXTRACT DATA ENABLES BUSINESS APPLICATIONS TO EXTRACT DATA INDEPENDENT OF SPECIFIC COMPUTER PROGRAMS INDEPENDENT OF SPECIFIC COMPUTER PROGRAMS* DBMS
15
7.15 Prof Jess Role @ UEAB 2010 COMPONENTS OF DBMS: DATA DEFINITION LANGUAGE:DATA DEFINITION LANGUAGE: –Defines data elements in database DATA MANIPULATION LANGUAGE:DATA MANIPULATION LANGUAGE: –Manipulates data for applications DATA DICTIONARY:DATA DICTIONARY: –Formal definitions of all variables in database, controls variety of database contents, data elements * DBMS
16
7.16 Prof Jess Role @ UEAB 2010 STRUCTURED QUERY LANGUAGE (SQL) EMERGING STANDARD DATA MANIPULATION LANGUAGE FOR RELATIONAL DATABASES * DBMS
17
7.17 Prof Jess Role @ UEAB 2010 ELEMENTS OF SQL SELECT: List of columns from tables desiredSELECT: List of columns from tables desired FROM: Identifies tables from which columns will be selectedFROM: Identifies tables from which columns will be selected WHERE: Includes conditions for selecting specific rows, conditions for joining multiple tablesWHERE: Includes conditions for selecting specific rows, conditions for joining multiple tables* DBMS
18
7.18 Prof Jess Role @ UEAB 2010 TWO VIEWS OF DATA BIT BYTE FIELD RECORD FILE DATABASE PHYSICAL VIEW: Where is data physically?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?LOGICAL VIEW: What data is needed by application? –SUCCESSION OF FACTS NEEDED BY APPLICATION –NAME, TYPE, LENGTH OF FIELD * DBMS
19
7.19 Prof Jess Role @ UEAB 2010 RELATIONAL DATA MODEL DATA IN TABLE FORMATDATA IN TABLE FORMAT RELATION: TABLERELATION: TABLE TUPLE: ROW (RECORD) IN TABLETUPLE: ROW (RECORD) IN TABLE FIELD: COLUMN (ATTRIBUTE) IN TABLEFIELD: COLUMN (ATTRIBUTE) IN TABLE*
20
7.20 Prof Jess Role @ UEAB 2010 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
7.21 Prof Jess Role @ UEAB 2010 ROOT FIRST CHILD 2nd CHILD RatingsSalary Compensation Job Assignments PensionInsuranceHealth Benefits Employer HIERARCHICAL DATA MODEL
22
7.22 Prof Jess Role @ UEAB 2010 NETWORK DATA MODEL VARIATION OF HIERARCHICAL MODELVARIATION OF HIERARCHICAL MODEL USEFUL FOR MANY-TO-MANY RELATIONSHIPSUSEFUL FOR MANY-TO-MANY RELATIONSHIPS* NETWORK A NETWORK B NETWORK C NETWORK 1 NETWORK 2
23
7.23 Prof Jess Role @ UEAB 2010 OTHER SYSTEMS LEGACY SYSTEM: older systemLEGACY SYSTEM: older system OBJECT - ORIENTED DBMS: stores data & procedures as objectsOBJECT - ORIENTED DBMS: stores data & procedures as objects OBJECT - RELATIONAL DBMS: hybridOBJECT - RELATIONAL DBMS: hybrid*
24
7.24 Prof Jess Role @ UEAB 2010 CREATING A DATABASE CONCEPTUAL DESIGNCONCEPTUAL DESIGN PHYSICAL DESIGNPHYSICAL DESIGN*
25
7.25 Prof Jess Role @ UEAB 2010 CREATING A DATABASE CONCEPTUAL DESIGN: ABSTRACT MODEL, BUSINESS PERSPECTIVEABSTRACT MODEL, BUSINESS PERSPECTIVE HOW WILL DATA BE GROUPED?HOW WILL DATA BE GROUPED? RELATIONSHIPS AMONG ELEMENTSRELATIONSHIPS AMONG ELEMENTS ESTABLISH END-USER NEEDSESTABLISH END-USER NEEDS*
26
7.26 Prof Jess Role @ UEAB 2010 DETAILED MODEL BY DATABASE SPECIALISTSDETAILED MODEL BY DATABASE SPECIALISTS ENTITY-RELATIONSHIP DIAGRAMENTITY-RELATIONSHIP DIAGRAM NORMALIZATIONNORMALIZATION HARDWARE / SOFTWARE SPECIFICHARDWARE / SOFTWARE SPECIFIC* CREATING A DATABASE PHYSICAL DESIGN:
27
7.27 Prof Jess Role @ UEAB 2010 ELEMENTS OF DATABASE ENVIRONMENT DATABASE MANAGEMENT SYSTEM DATA ADMINISTRATION DATABASE TECHNO LOGY & MANAGEMENT USERS DATA PLANNING & MODELING METHODOLOGY
28
7.28 Prof Jess Role @ UEAB 2010 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
7.29 Prof Jess Role @ UEAB 2010 NORMALIZATION PROCESS OF CREATING SMALL DATA STRUCTURES FROM COMPLEX GROUPS OF DATA EXAMPLES: ACCOUNTS RECEIVABLEACCOUNTS RECEIVABLE PERSONNEL RECORDSPERSONNEL RECORDS PAYROLLPAYROLL*
30
7.30 Prof Jess Role @ UEAB 2010 DISTRIBUTED DATABASES PARTITIONED: remote CPUs (connected to host) have files unique to that site, e.g., records on local customersPARTITIONED: 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 formsDUPLICATE: each remote CPU has copies of common files, e.g., layouts for standard reports and forms*
31
7.31 Prof Jess Role @ UEAB 2010 DATABASE ADMINISTRATION DEFINES & ORGANIZES DATABASE STRUCTURE AND CONTENTDEFINES & ORGANIZES DATABASE STRUCTURE AND CONTENT DEVELOPS SECURITY PROCEDURESDEVELOPS SECURITY PROCEDURES DEVELOPS DATABASE DOCUMENTATIONDEVELOPS DATABASE DOCUMENTATION MAINTAINS DBMSMAINTAINS DBMS*
32
7.32 Prof Jess Role @ UEAB 2010 DATABASE TRENDS MULTIDIMENSIONAL DATA ANALYSIS: 3D (or higher) groupings to store complex dataMULTIDIMENSIONAL DATA ANALYSIS: 3D (or higher) groupings to store complex data HYPERMEDIA: Nodes contain text, graphics, sound, video, programs. organizes data as nodes.HYPERMEDIA: Nodes contain text, graphics, sound, video, programs. organizes data as nodes.*
33
7.33 Prof Jess Role @ UEAB 2010 DATABASE TRENDS DATA WAREHOUSE: Organization ’ s electronic library stores consolidated current & historic data for management reporting & analysisDATA WAREHOUSE: Organization ’ s electronic library stores consolidated current & historic data for management reporting & analysis ON-LINE ANALYTICAL PROCESSING (OLAP): Tools for multi- dimensional data analysisON-LINE ANALYTICAL PROCESSING (OLAP): Tools for multi- dimensional data analysis*
34
7.34 Prof Jess Role @ UEAB 2010 COMPONENTS OF DATA WAREHOUSE
35
7.35 Prof Jess Role @ UEAB 2010 DATABASE TRENDS DATA MART: Small data warehouse for special function, e.g., Focused marketing based on customer infoDATA 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 trendsDATAMINING: Tools for finding hidden patterns, relation- ships, for predicting trends*
36
7.36 Prof Jess Role @ UEAB 2010 DATABASE TRENDS LINKING DATABASES TO THE WEB: WEB USER CONNECTS TO VENDOR DATABASEWEB USER CONNECTS TO VENDOR DATABASE SPECIAL SOFTWARE CONVERTS HTML TO SQLSPECIAL SOFTWARE CONVERTS HTML TO SQL SQL FINDS DATA, SERVER CONVERTS RESULT TO HTMLSQL FINDS DATA, SERVER CONVERTS RESULT TO HTML*
37
7.37 Prof Jess Role @ UEAB 2010 MANAGING DATA DATARESOURCES
Similar presentations
© 2024 SlidePlayer.com. Inc.
All rights reserved.