DATA BASE:
THE ORGANIZATION'S TOTAL COLLECTION OF DATA ON COMPUTER STORAGE DEVICES
DATA BASE MANAGEMENT SYSTEM:
COLLECTION OF SOFTWARE SPECIALLY DESIGNED TO MANAGE DATA IN A DATA BASE ACCORDING TO REQUESTS ISSUED BY APPLICATION PROGRAMS OR DIRECTLY BY USERS
DATA BASE:
IS A CENTRAL POOLED STORE OF DATA THAT CAN BE ACCESSED AS NEEDED BY ALL ACCOUNTING APPLICATIONS
"ONE BIG FILE" CONCEPT
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ACCOUNTANTS NEED TO UNDERSTAND DATABASES BECAUSE:
1. DBMS CAUSE STRUCTURAL CHANGES
IN ACCOUNTING SYSTEMS
2. IMPROVE FINANCIAL REPORTING AND
DECISION MAKING
3. KNOWING HOW THEY WORK AND HOW LOGICAL DATA STRUCTURES ARE CONSTRUCTED IS ESSENTIAL TO BEING A PARTICIPANT IN SYSTEMS DESIGN TEAM
4. DBMS RAISE NEW CONCERNS OF INTERNAL CONTROL
WHETHER TO USE THE CONVENTIONAL FILE SYSTEM VS. DBMS IS A KEY DECISION IN THE PLANNING PROCESS
TO DO THIS MUST EVALUATE ADVANTAGES AND DISADVANTAGES OF EACH TO THE ORGANIZATION
ADVANTAGES AND DISADVANTAGES OF CONVENTIONAL FILE BASED SYSTEM
ADVANTAGES
WORK WELL IN SMALL SIMPLE AIS
CONCEPTUALLY SIMPLE
READILY UNDERSTOOD AND OPERATED
CONTROL PROBLEMS USUALLY EASY TO SOLVE
DIRECTLY ANALOGOUS TO JOURNALS AND LEDGERS OF MANUAL AIS
DISADVANTAGES
FILE OWNERSHIP BY DIFFERENT ACCOUNTING APPLICATIONS
COMPLICATED TO DEVELOP AND MAINTAIN
INFLEXIBLE TO ANSWER UNANTICIPATED USER REQUESTS
PROGRAMMING COMPLEXITY
DATA DEPENDENCY OF THE APPLICATION
DATA REDUNDANCY - EXCESSIVE STORAGE
POOR DATA INTEGRATION BETWEEN APPLICATIONS
DIFFICULT TO MAINTAIN:
GOOD DATA QUALITY - MULTIPLE ENTRIES OF SAME DATA ITEM - CHANGES
DATA INCONSISTENT
INEFFICIENT USE OF RESOURCES
ADVANTAGES AND DISADVANTAGES OF DATA BASE MANAGEMENT SYSTEM
ADVANTAGES
PROGRAMMING SIMPLIFICATION
-SIMPLIFY/ELIMINATE APPLICATION PROGRAMS
DATA INDEPENDENCE
APPLICATION PROGRAMS COMMUNICATE WITH DBMS RATHER THAN THE DATA -
DATA INTEGRATION
DATA QUALITY AND EFFICIENCY
DATA SECURITY
DISADVANTAGES
HIGH SOFTWARE COST
INCREASED HARDWARE REQUIREMENTS -
LARGE NUMBER OF INSTRUCTIONS
REQUIRED TECHNICAL SKILLS
DIFFICULT CONVERSION FROM CONVENTIONAL FILE SYSTEMS
VULNERABILITY TO SYSTEMS FAILURE -
ALL APPLICATIONS DEPEND ON DBMS
POTENTIAL FOR ERROR CONTAMINATION
LOOK AT HANDOUT
HOW A DATA REQUEST IS HANDLED BY THE DBMS
1. THE APPLICATION PROGRAM OR THE USER REQUESTS DATA ELEMENT THROUGH DML
2. THE DML VALIDATES THE AUTHORITY TO MAKE SUCH REQUEST. IF AUTHORIZED, THE DML FORWARDS THE REQUEST TO FILE ACCESS SUB-ROUTINES.
3. FILE ACCESS SUB ROUTINES DETERMINE WHERE REQUESTED DATA ELEMENT IS STORED AND FORWARDS THIS INFO TO THE OPERATING SYSTEM.
4. THE OPERATING SYSTEM USES THE INFORMATION FROM THE DBMS AND ADDS SUPPLEMENTARY INFO OF ITS OWN TO DETERMINE EXACT PHYSICAL LOCATION OF THE DATA ON DISK.
5. OPERATING SYSTEM SENDS THE DATA TO THE DML SUB-ROUTINES.
6. DML SUBROUTINES SEND DATA TO THE APPLICATION PROGRAM OR THE USER.
THREE LEVEL ARCHITECTURE OF A DBMS
1. EXTERNAL LEVEL
USER'S LOGICAL VIEW OF PORTION OF DATA
2. CONCEPTUAL LEVEL
USER'S LOGICAL VIEW OF ALL DATA
3. INTERNAL LEVEL
STORAGE VIEW OF ALL DATA
SCHEMA
THE VIEW OF THE DATA AND THEIR RELATIONSHIPS IN A DATA BASE
EXTERNAL AND INTERNAL SCHEMA
FOLLOW THE THREE LEVELS OF THE ABOVE ARCHITECTURE
EXTERNAL SCHEMA IS THE USER'S LOGICAL VIEW OF THE DBMS
INTERNAL SCHEMA DESCRIBES HOW THE CONCEPTUAL SCHEMA IS IMPLEMENTED PHYSICALLY
REFERS TO THE PHYSICAL LOCATION OF THE DATA
MAPPING
DONE BY THE DBMS
MAKES THE DATA ELEMENT IN 1 SCHEMA CORRESPOND TO AN ELEMENT IN ANOTHER SCHEMA
DATA RELATIONSHIPS
RELATIONSHIPS AMONG DATA ELEMENTS
NO RELATIONSHIP
ONE TO ONE
PRODUCT NUMBER AND DESCRIPTION
ONE TO MANY
ONE CUSTOMER TO MANY INVOICES
MANY TO ONE
REVERSE DIRECTION OF ABOVE
MANY TO MANY
CUSTOMERS AND PRODUCTS
DATA BASE MODELS
DESCRIBE THE ARCHITECTURE OF THE DATA BASE AT THE CONCEPTUAL LEVEL
HIERARCHIAL
OLDEST - TREE DATA STRUCTURE
SINGLE NODE CALLED PARENT
NODES BELOW CALLED CHILD
ONLY FOR ONE TO ONE AND ONE TO MANY RELATIONSHIPS - NO LINKAGES BETWEEN RECORDS AT SAME LEVEL OF THE HIERARCHY
CAN NOT HANDLE INQUIRIES THAT ARE MANY TO MANY
NETWORK
NO DISTINCT HIERARCHY
CAN HANDLE ALL TYPES OF RELATIONSHIPS
RELATIONAL
DATA ARE PERCEIVED BY THE USER TO BE STRUCTURED IN THE FORM OF FLAT FILES OR TABLES
EACH TABLE CONSISTS OF RECORDS COMPRISED OF A KEY AND NONKEY ELEMENTS
TABLES GIVE THE USER THE ILLUSION OF DISTINCT FILES
DATA NORMALIZATION
HELPS TO DEFINE THE BEST WAY TO ARRANGE THE TABLES OF THE DATA BASE
ENSURES THE STABILITY OF THE DATA BASE OVER TIME AND MINIMIZES REDUNDANCY AND INCONSISTENCY
STEPS TO NORMALIZE DATA:
1. PLACE ALL REPEATED DATA ELEMENTS IN SEPARATE TABLES AND ASSIGN APPROPRIATE KEYS
2. PLACE ALL NON-KEY ELEMENTS - THAT ARE SPECIFIED BY SOMETHING OTHER THAN THE COMPLETE KEY - IN SEPARATE TABLES
3. ELIMINATE REDUNDANCY
ELIMINATE REDUNDANT DATA ELEMENTS AND REDUNDANT TABLES - ANY TABLE THAT IS A SUBSET OF ANOTHER
WAYS TO DESIGN A DATA BASE
ENTITY-RELATIONSHIP MODELING
CALLED E-R
HIGH LEVEL CONCEPTUAL MODEL
INDEPENDENT OF PARTICULAR DBMS
TOP DOWN VS. BOTTOM-UP APPROACH OF RELATIONAL TABLES
1. SELECT THE ENTITIES AND THE RELATIONSHIPS BETWEEN THEM THAT ARE OF INTEREST TO THE ORGANIZATION
2. ASSIGN ATTRIBUTES TO THE ENTITIES AND RELATIONSHIPS SO THAT A FULLY NORMALIZED SET OF TABLES IS OBTAINED
THE FOLLOWING SYMBOLS REPRESENT THE VARIOUS COMPONENTS OF AN E--R DIAGRAM
1. A RECTANGLE REPRESENTS AN ENTITY
2. AN ELLIPSE REPRESENTS AN ATTRIBUTE
3. A DIAMOND REPRESENTS A RELATIONSHIP
4. A LINE LINKS:
ATTRIBUTE TO ENTITY
ENTITY TO RELATIONSHIP
ATTRIBUTE TO RELATIONSHIP
RETRIEVAL OF DATA FROM DATA BASES
POINTERS ARE GENERALLY USED FOR RETRIEVING DATA IN HIERARCHIAL AND NETWORK DATA BASES
ATTRIBUTES ARE USED IN RELATIONAL DATA BASES
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