Ais Test Ch 4 And 17

Front 1

Benefits of using database systems

Back 1

1. data integration and sharing

2. minimal data redundancy

3. cross-functional analysis and reporting

Front 2

Database systems > file-oriented

Back 2

Database systems separate physical and logical views. This facilitates developing new applications using a logical view

Front 3

Difference between file-oriented and relational

Back 3

File-oriented: more unstructured data store for arbitrary, unrelated data. More general

Relational: built on top of the general data storage services provided by file systems

Front 4

Difference between logical and physical view

Back 4

Logical: how people conceptually organize and understand the data

Physical: how and where data are physically arranged an stored in the computer system.

Front 5

3 types of schemas

Back 5

conceptual, external, internal

Front 6

Conceptual-level schema

Back 6

organization wide view of entire database listing all data elements and relationships between them

Front 7

External-level schema

Back 7

set of individual user views of subschemas

Front 8

Internal-level schema

Back 8

provides a low level view of database including descriptions about pointer,s indexes, record lengths, etc

Front 9

Role of accountants in the development of schemas

Back 9

involved in conceptual and external levels

Front 10

Data dictionary- def

Back 10

the "blueprint" of the structure of the database and includes data elements, field types, programs that use the elements, outputs, etc.

Front 11

How does a DBMS facilitate creating, changing, and querying data

Back 11

-creating data through DDL

-changing data through DML

-querying data through DQL

Front 12

4 DMBS languages- who uses each

Back 12

-DDL and DML used by authorized administrators and programmers

-DQL and Report writer used by users

Front 13

DDL (data definition language)

Back 13

builds the data dictionary, creates the database, describes logical view for users and specifies records or field security constraints

Front 14

DML (data manipulation language)

Back 14

changes database content, including data element updates, insertions, and deletions

Front 15

DQL (data query language)

Back 15

contains powerful, easy to use commands that enable users to receive, sort, order, and display data

Front 16

Report Writer

Back 16

simplifies report creation

Front 17

What sort of info is contained in the data dictionary

Back 17

new or deleted data elements and changes in data element names, descriptions, or uses

-ex: records containing a specific data item, source of the data item, field type

Front 18

Primary key

Back 18

uniquely define a specific row in a table

Front 19

Foreign key

Back 19

used to link tables

Front 20

Other nonkey attributes

Back 20

store info about that entity

Front 21

2 advantages of semantic data modeling over normalization

Back 21

1. facilitates efficient design of transaction processing databases.

2. facilitates communication with system users, which helps ensure the new system meets users' actual needs

Front 22

How does redundancy apply to database design

Back 22

Databases store all data in one uniform data which leads to redundancy, which makes fie maintenance time-consuming and error prone

Front 23

Explain the relational database data model

Back 23

represents conceptual and external-level schemas as if data are store in tables, in the manner described in the internal-level schema

Front 24

4 basic requirements when logically designing a relational database model

Back 24

1. every column in a row must be single valued

2. primary keys cannot be null

3. foreign keys must have values that correspond to the value of the primary key in another table

4. all nonkey attributes must describe a characteristic of the object identified by the primary key

Front 25

What is meant by, "Accountants can and should participate in all stages of the database design process"

Back 25

make sure steps are followed properly

Front 26

Describe an REA data model

Back 26

-developed specifically for use in designing AIS

-provides guidance for database design by identifying what entities should be included and prescribing how to structure relationships

Front 27

Define cardinality

Back 27

describe the nature of the relationship between 2 entities by indicating how many instances of one entity can be linked to each specific instance of another entity

Front 28

Steps in developing an REA diagram

Back 28

-identify events about which management wants to collect info

-identify the resources affected by each event and the agents who participate in those events

-determine the cardinalities of each relationship

Front 29

Explain how an AIS system can be viewed as a set of "give-to-get" exchanges

Back 29

-events must be linked to at least one resource that they affect

-"Get"= increase quantity of inventory and amount of cash

-"Give"= decrease quantity of inventory and amount of cash

Front 30

Define min and max cardinalities

Back 30

1:1= max cardinality for each entity is 1

1:N= max of 1 entity is 1 and other is many

M:N= max for both is many

Front 31

DBMS

Back 31

-links the way data are physically stored with each user's logical view of the data

-allows users to access, query, or update the database with out reference to how or where data are physically stored

Front 32

Data warehouse

Back 32

contains detailed and summarized data for many years and used for analysis

Front 33

Business intelligence

Back 33

using a data warehouse for strategic decision making

Front 34

2 types BI

Back 34

data mining and OLAP

Front 35

Data mining

Back 35

using statistical analysis to discover unhypothesized relationships

Front 36

OLAP

Back 36

using queries to guide the investigation of hypothesized relationships

Front 37

Update/insert/delete anomaly

Back 37

update- when data values are recorded incorrectly

insert- when certain attributes can't be inserted without the presence of other attributes

delete- when deleting a row has unintended consequences

Front 38

Two approaches to database design

Back 38

normalization and semantic data modeling

Front 39

Normalization

Back 39

assumes everything is initially stored in one large table and decomposed into a set of tables

Front 40

3NF

Back 40

set of tables free of anomalies

Front 41

Database design process (5 steps)

Back 41

1. system analysis

2. conceptual design

3. physical design

4. implementation and conversion

5. operation and maintenance

Front 42

ER diagrams

Back 42

-graphical technique for portraying a database schema

- shows the various entities being modeled and the important relationships among them

Front 43

"R"

Back 43

resources- have economic value to the organization

ex: cash, inventory

Front 44

"E"

Back 44

events- various business activities that management wants to collect info on

ex: sales, purchases, payroll, receive/disburse cash

Front 45

"A"

Back 45

agents- people and organizations that participate in events about whom info is desired for planning, control, and evaluation purposes

ex: employees, customers, suppliers

Front 46

A well-structured relational database

Back 46

every tables must be related to at least one other table

Front 47

What stage of the database design process is data modeling

Back 47

system analysis, conceptual design, physical design