1. Database Management Systems
Chapter 9
Database Management Systems
Accounting Information Systems, 5th edition
James A. Hall 1

2. 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.

3. File-Oriented (Flat-File) Environment
Data
User 1(Sales)
Transactions
Program 1
A,B,C
User 2 (A/R)
Transactions
Program 2
X,B,Y
User 3 (Payroll)
Transactions
Users access data via computer programs that process the data and present information to the users.
Users own their data files.
Data redundancy results as multiple applications maintain the same data elements.
Files and data elements used in more than one application must be duplicated, which results in data redundancy.
As a result of redundancy, the characteristics of data elements and their values are likely to be inconsistent.
Outputs usually consist of preprogrammed reports instead of ad-hoc queries provided upon request. This results in inaccessibility of data.
Changes to current file-oriented applications cannot be made easily, nor can new developments be quickly realized, which results in inflexibility.
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. 3

4. Database Approach Database Program 1 A, B, D C, B X, M Y, S L,
User 1 (Sales)
Transactions
Program 1 A, B, C, X, Y, L, M D B M S
User 2 (A/R)
Transactions
Program 2
User 3 (Payroll)
Transactions
Solves the following problems of the flat file approach
no data redundancy - except for primary keys, data is only stored once
single update
current values
task-data independence - users have access to the full domain of data available to the firm
A database is a set of computer files that minimizes data redundancy and is accessed by one or more application programs for data processing.
The database approach to data storage applies whenever a database is established to serve two or more applications, organizational units, or types of users.
A database management system (DBMS) is a computer program that enables users to create, modify, and utilize database information efficiently.
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.] 6

5. 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 4

6. 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.

7. 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)

8. 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 7

9. Query Language
Query capability permits both end users and professional programmers to access data (information) in database without writing conventional programs. 13

10. Three Steps in Designing a Database
Prepare conceptual model
Identify entities
Identify relationships between entities
Prepare ER diagram (ERD)
Specify logical design
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

11. Prepare the Conceptual Model
Phase 1
Prepare the Conceptual Model
Draw an ERD to capture the process. 1

12. Example of a Relationship Linking Two Entities
places
CUSTOMER
ORDER
Name
Order Number
Date
Cust Number
Example of 1:M relationship, using Crow’s Feet notation. We usually don’t cover the “0” relationship.

13. Specify Logical Design
Phase 2
Specify Logical Design
Create relational tables. 1

14. 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.

15. 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 31

16. 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) 32

17. 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. 33

18. 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. 79

19. 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. 38

20. 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). 38

21. all nonkey attributes (fields) in table are dependent on primary key (PK)
Student ID
Lname
Fname
Major
CRN
Course
Instructor ID
80012
Garcia
Maria
ACCT
17256
ACCT3321
G001
17535
ACCT3320
G003
17004
MKT3311
G005
80014
Henry
Hank
MKT
17155
80020
Hernandez
Barbara
CIS
17200
CIS2320
G010
80033
Johnson
Kris
ECON
16256
S001
17005
ECON3315
S005
16500
CIS3545
M001
This is an unnormalized table. Only Lname & Fname depend on the PK of
Student ID. Other fields belong in another table(s).

22. Steps in Normalization
Unnormalized Table
with repeating groups
1. Remove
repeating
groups
Does field depend on PK? If no, remove and put in another table.
First normal
form (1NF)
2. Remove
partial
dependencies
Only concerns tables with composite PKs. See Fig. 9-38
Second normal
form (2NF)
3. Remove
transitive
dependencies
Third normal
form (3NF)
When field depends on another non-key field in table. See Fig. 9-40 86

23. 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. 40

24. Implement Physical Design
Phase 3
Implement Physical Design
Decide about software and hardware. 1

25. Distributed Data Processing

26. President
CENTRALIZED COMPUTER
SERVICES FUNCTION VP
Marketing
VP Computer
Services VP
Operations VP
Finance
Systems
Development
Database
Administration
Data
Processing
New Systems
Development
Data
Control
Data
Preparation
Data
Library
Systems
Maintenance
Computer
Operations
DISTRIBUTED ORGANIZATIONAL
STRUCTURE
President VP
Marketing VP
Finance VP
Administration VP
Operations
Manager
Plant X
Manager
Plant Y
Treasurer
Controller
IPU
IPU
IPU
IPU
IPU
IPU

27. 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
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
1 DDP = Distributed Data Processing

28. 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

29. 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.

30. 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

31. 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.

32. 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.

33. 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. The End!