Mis 2Nd Midterm

Front 1

transaction processing

Back 1

early business IS designed to collect and store data related to accting & financial transactions only. triggered by economic events

Front 2

problems associated with transaction based approach

Back 2

-limited data are collected
- important data ay have no direct financial impact
-modern data needs are extensive and complex.
-financial transaction processing doesn't meet these needs.

Front 3

Event processing

Back 3

business events are not necessarily associated with economic impacts
-collect when when business even occurs
-organization defines "business event"
-could use dfd to determind inputs

Front 4

transaction processing

Back 4

financial transactions
-direct, measurable economic impacts
-data needs are driven by specific sysems, function areas and processes

Front 5

event processing

Back 5

collect more complex data
-organization wide data needs

Front 6

file mgmt

Back 6

collecting, organizing, storing, retrieving and manipulating data maintained in a file oriented data processing environment. not the same thing as a database.

Front 7

flat file

Back 7

each different typle of transaction has a separate fild associated with it.

Front 8

problems with flat file systesm

Back 8

1)data redundancy. ok if back up.
2)data integrity - data have not been altered
3)data independence - separating data from programs that use it
4) poor data control/ difficult maintenance
5)privacy

Front 9

schema

Back 9

complete description of the configuration of record tpes and data items. defines the logical structure and organizational view of the data

Front 10

subschema

Back 10

- a description of a portion of a chema DMBS map each user's view of the data from subschemas to schemas

Front 11

DBMS

Back 11

set of computer programs that controls the creation, maintenance and the use of the database in a computer platform or of an org and its end users

Front 12

query language

Back 12

used to access DB and produce inquiry reports

Front 13

logical view

Back 13

how data appear to end user (table)

Front 14

physical

Back 14

physical storage of data

Front 15

lost update problem

Back 15

multiple simultaneous users

Front 16

enterprise

Back 16

large organizational db with many users

Front 17

personal

Back 17

smaller simplistic db that could be run on a pc

Front 18

character

Back 18

a letter or number

Front 19

field

Back 19

a collection of related chars such as customer number (column)

Front 20

record

Back 20

colelction of related data fields associated with a perticular person (row)

Front 21

file

Back 21

a collection of related records

Front 22

record layout

Back 22

describes the fields making the record

Front 23

metadata

Back 23

data that describe data

Front 24

relationship

Back 24

a connection between individual records in a table and between records in other tables

Front 25

attribute

Back 25

a property or character whose value describes each entity in an entity set

Front 26

simple attribute

Back 26

cant be broken down

Front 27

composite attribute

Back 27

can break down further

Front 28

identifier attribute

Back 28

something that has to be unique to everyone

Front 29

single valued attribute

Back 29

student dob

Front 30

multivalued attribute

Back 30

studnet phone

Front 31

model

Back 31

a copy or representation of something

Front 32

dfd

Back 32

business processes and data flows

Front 33

erd

Back 33

"data base" blueprint for relational db structure. how data are represented and stored

Front 34

3 reasons to model a system

Back 34

focus, communicate, verify

Front 35

data model

Back 35

a graphical textual representation of data we want to store, retrieve and manipulate.

Front 36

entity

Back 36

a single object, a row in a db, a single instance of an entity set

Front 37

entity set

Back 37

a colelction of related objects, a table

Front 38

key

Back 38

a single attribute or set of attributes that uniquely id each ientity in a table

Front 39

domain

Back 39

acollection of all possible legal values an attribue may take

Front 40

degree

Back 40

number of entity sets in a relationships. unary/binary/ternary

Front 41

dfd

Back 41

process modelign

Front 42

erd

Back 42

data modeling

Front 43

entity integrity

Back 43

guarantees each entity in a table has a unique value

Front 44

regerential integrity

Back 44

the attribue value on the amny side of the relationship

Front 45

normalization

Back 45

process of minimizing the duplication of information. corrects logical and structural problems

Front 46

higher levels of normalization

Back 46

> slower processing.
-more tables and more relationships between tables. more time required to find a piece together data from queries

Front 47

normalization

Back 47

there is generally a tradeoff between higher levels of normalization and speed. as redundancy is reduced, the time it takes a the db to process a query typically increases

Front 48

foreign key

Back 48

many side

Front 49

primary key

Back 49

needed in both tables

Front 50

multi-valued attribute

Back 50

a field/colum that can have multiple values in a single space or cell