Chapter 9
Database
Management
Systems
Accounting Information Systems, 5th edition
James A. Hall
1
Flat-File Versus Database Environments



Computer processing involves two components: data and
instructions (programs).
Conceptually, there are two methods for designing interface
between programs and data:
 file-oriented (flat-file) processing: A specific data file
was created for each application [legacy systems]
 data-oriented processing: Create a single data repository
to support numerous applications [current systems]
Disadvantages of file-oriented processing include redundant
data and programs and varying formats for storing the
redundant data.
File-Oriented (Flat-File) Environment
User 1(Sales)
Transactions
Data
Program 1
A,B,C
User 2 (A/R)
Transactions
Program 2
X,B,Y
User 3 (Payroll)
Transactions
Program 3
L,B,M
Where B is a customer record. Assume B’s address changes. Each user
that works with the B record must modify the address, increasing chance for error.
Database Approach
User 1 (Sales)
Transactions
Database
Program 1
User 2 (A/R)
Transactions
Program 2
User 3 (Payroll)
Transactions
D
B
M
S
A,
B,
C,
X,
Y,
L,
M
Program 3
With the database approach, any User could change B’s address - it would be
changed for all users. changes. [Assume all users have authority to change the
address for this example.]
Data Redundancy & Flat-File Problems




Data Storage - creates excessive storage costs of
paper documents and/or magnetic form
Data Updating - any changes or additions must be
performed multiple times (see example of B’s
address)
Currency of Information - potential problem of
failing to update all affected files
Task-Data Dependency - user’s inability to obtain
additional information as his or her needs change
Advantages of the Database
Approach
Data sharing/centralized database resolves flat-file problems:




No data redundancy - Data stored only once, eliminating
data redundancy and reducing storage costs.
Single update - Because data are in only one place,
requires only single update procedure, reducing time/cost
of keeping database current.
Current values - Change to database made by any
(authorized) user yields current data values for all other
(authorized) users.
Task-data independence - As users’ information needs
expand beyond immediate domain, new needs can be
more easily satisfied than under flat-file approach.
6
Disadvantages of the
Database Approach

Can be costly to implement


additional hardware, software, storage, and
network resources are required – yet these costs
continue to drop…
Can only run in certain operating
environments

may be unsuitable for some existing system
configurations (e.g., legacy systems)
7
Internal Controls and DBMS1


Purpose of DBMS is to provide controlled
access to database.
DBMS is special software programmed to
know which data elements each user is
authorized to access and deny unauthorized
requests of data.
1 DBMS
= database management system
8
Query Language

Query capability permits both end users and
professional programmers to access data
(information) in database without writing
conventional programs.
9
Three Steps in Designing a Database
1.
Prepare conceptual model



2.
Specify logical design


3.
Identify entities
Identify relationships between entities
Prepare ER diagram (ERD)
Select logical database model (which will always be
relational nowadays)
Transform conceptual data model using logical
database model
Implement physical design


Physical structures
Access methods
10
Phase 1
Prepare the Conceptual Model
Draw an ERD to
capture the
process.
11
Example of a Relationship Linking
Two Entities
places
CUSTOMER
Name
ORDER
Order Number
Cust Number
Example of 1:M relationship, using Crow’s Feet
notation. We usually don’t cover the “0” relationship.
Date
Phase 2
Specify Logical Design
Create relational
tables.
13
Logical Data Structures


Objective is to develop structure efficiently so
data can be accessed quickly and easily.
Four types of database structures are:




hierarchical (tree structure)
network
relational
object-oriented
Concentrate on relational
DBs. They are the systems
being created at the current
time.
14
The Relational Model

Relational model portrays data in form of two
dimensional tables (looks like Excel
worksheet):




relation - database table
attributes/fields (data elements) - columns
tuples (records) - rows
data - intersection of rows and columns
15
Properly Designed Relational Tables




No repeating values – Primary Key cannot
repeat in a table.
Attribute values in any column must all be of
same class. [can’t put text in a date field]
Each column (field name) in a table must be
uniquely named. [can’t have 2 address fields
both named Address – use Addr1 and Addr2]
Each row (record) in a table must be unique in
at least one attribute (primary key)
16
Relational Model Data Linkages (>1 table)



No explicit pointers are present – data are viewed as collection of
independent tables.
“Relations” formed by attribute/field that is common to both
tables in relation. This field is a “foreign key.”
How to assign foreign keys:
 if 1:1 association, either of table’s primary keys may be foreign
key.
 if 1:M association, primary key of the ONE side is embedded as
foreign key in the MANY side.
 if M:M (M:N) association, create separate linking table.
17
Three Types of Anomalies
(anomalies are found in Unnormalized tables)




Insertion Anomaly: New item
cannot be added to table until at least
one entity uses particular attribute
item.
Deletion Anomaly: If attribute item
used by only one entity is deleted, all
information about that attribute item
is lost.
Update Anomaly: Modification on
attribute must be made in each of
rows in which attribute appears.
Anomalies can be corrected by
creating relational tables.
18
Relational Tables


Various items of interest (customers,
inventory, sales) stored in SEPARATE tables
in database.
Advantages:



Removes all three anomalies
Efficient use of space.
Flexible. Users can form ad hoc relationships for
queries.
19
Normalization Process

Process that breaks up large, complex tables
into smaller tables that meet two conditions:



all nonkey attributes (fields) in table are
dependent on primary key (PK)
all nonkey attributes (fields) are independent of
other nonkey attributes (fields)
When unnormalized tables are split and
reduced to third normal form, they are linked
together by foreign keys (secondary keys).
20
all nonkey attributes (fields) in table are dependent on primary key (PK)
Student
ID
Course
Instructor
ID
17256
ACCT3321
G001
ACCT
17535
ACCT3320
G003
Maria
ACCT
17004
MKT3311
G005
Henry
Hank
MKT
17155
MKT3311
G005
80020
Hernandez
Barbara
CIS
17200
CIS2320
G010
80020
Hernandez
Barbara
CIS
17155
MKT3311
G005
80033
Johnson
Kris
ECON
16256
ACCT3321
S001
80033
Johnson
Kris
ECON
17005
ECON3315
S005
80033
Johnson
Kris
ECON
16500
CIS3545
M001
Lname
Fname
Major
80012
Garcia
Maria
ACCT
80012
Garcia
Maria
80012
Garcia
80014
CRN
This is an unnormalized table. Only Lname & Fname depend on the PK of
Student ID. Other fields belong in another table(s).
21
Steps in Normalization
Unnormalized Table
with repeating groups
First normal
form (1NF)
Second normal
form (2NF)
Third normal
form (3NF)
1. Remove
repeating
groups
Does field depend on PK? If no,
remove and put in another table.
Only concerns tables
with composite PKs.
See Fig. 9-38
When field depends on
another non-key field in
table. See Fig. 9-40
2. Remove
partial
dependencies
3. Remove
transitive
dependencies
Accountants and Data Normalization




Update anomalies can generate conflicting and obsolete
database values.
Insertion anomalies can result in unrecorded
transactions and incomplete audit trails.
Deletion anomalies can cause loss of accounting records
and destruction of audit trails.
Accountants should understand data normalization
process and be able to determine whether database is
properly normalized.
Phase 3
Implement Physical Design
Decide about
software and
hardware.
24
Distributed Data Processing
25
President
CENTRALIZED COMPUTER
SERVICES FUNCTION
VP
Marketing
VP Computer
Services
Systems
Development
New Systems
Development
Database
Administration
DISTRIBUTED ORGANIZATIONAL
STRUCTURE
IPU
Data
Control
Systems
Maintenance
VP
Marketing
VP
Operations
VP
Finance
Data
Processing
Data
Computer
Preparation Operations
Data
Library
President
VP
Finance
VP
Administration
Treasurer
Controller
IPU
IPU
VP
Operations
Manager
Plant X
IPU
IPU
Manager
Plant Y
IPU26
Characteristics of DDP1
Advantages:




Cost reductions in
hardware and data entry
tasks
Improved cost control
responsibility
Improved user satisfaction
because control is closer to
user level
Backup of data can be
improved through use of
multiple data storage sites
1 DDP
= Distributed Data Processing
Disadvantages






Loss of control
(organization-wide)
Mismanagement of
organization-wide resources
Hardware/software
incompatibility
Redundant tasks/data
Incompatible tasks may be
consolidated
Lack of standards
27
Centralized Databases in DDP
Environment




Data are retained in central location.
Remote IPUs (workstations) send requests
for data.
Central site services needs of remote
workstations.
Actual data processing is performed at remote
workstation
28
Data Currency



Can be an issue in DDP with centralized database
During transaction processing, data will temporarily
be inconsistent as record is being read and updated.
Database lockout procedures are necessary to
keep workstations from reading inconsistent data
and/or from writing over a transaction being written
by another workstation.
29
Distributed Databases: Partitioning


Splits central database into segments that are distributed
to their primary users
Advantages:
 users’ control is increased by having data stored at
local sites
 transaction processing response time is improved
 volume of transmitted data between workstations is
reduced
 Reduces potential data loss from a disaster
Distributed Databases: Replication


Duplication of entire database for multiple
workstations
Effective for situations with a high degree of
data sharing, but no primary user


supports read-only queries.
Data traffic between sites is reduced
considerably.
The Deadlock Phenomenon



Especially a problem with partitioned databases
Occurs when multiple sites lock each other out
of data that they are currently using
Special software needed to analyze and resolve
conflicts.
32
The Deadlock Phenomenon
Locked A, waiting for C
Locked E, waiting for A
A,B
E, F
C,D
Locked C, waiting for E
34