1. Database Management Systems
Chapter 9
Database Management Systems 1

2. Objectives for Chapter 9
Operational problems inherent in the flat file approach to data management that gave rise to the database concept
The relationships among the defining elements of the database environment
The anomalies caused by unnormalized databases and the need for data normalization
The stages in database design including entity identification, data modeling, constructing the physical database, and preparing user views
The operational features of distributed databases and recognize the issues that need to be considered in deciding on a particular database configuration 31

3. Flat-File Versus Database Environments
Computer processing involves two components: data and instructions (programs).
Conceptually, there are two methods for designing the interface between program instructions and data:
file-oriented processing: A specific data file was created for each application
data-oriented processing: Create a single data repository to support numerous applications.
Disadvantages of file-oriented processing include redundant data and programs and varying formats for storing the redundant data.
The format for similar fields may vary because the programmer used inconsistent field formats.

4. Flat-File Environment
Data
User 1
Transactions
Program 1
A,B,C
User 2
Transactions
Program 2
X,B,Y
User 3
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 3

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
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. Database Approach Database Program 1 A, B, D C, B X, M Y, S L,
User 1
Transactions
Program 1 A, B, C, X, Y, L, M D B M S
User 2
Transactions
Program 2
User 3
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 6

7. Advantages of the Database Approach
Data sharing/centralize database resolves flat-file problems:
No data redundancy - Data is stored only once, eliminating data redundancy and reducing storage costs.
Single update - Because data is in only one place, it requires only a single update procedure, reducing the time and cost of keeping the database current.
Current values - A change to the database made by any user yields current data values for all other users.
Task-data independence - As users’ information needs expand beyond their immediate domain, the new needs can be more easily satisfied than under the flat-file approach.

8. Disadvantages of the Database Approach
Can be costly to implement
additional hardware, software, storage, and network resources are required
Can only run in certain operating environments
may make it unsuitable for some system configurations
Because it is so different from the file-oriented approach, the database approach requires training users
may be inertia or resistance

9. Elements of the Database Approach
Administrator
System Development
Process
System Requests
Applications
User
Programs
DBMS
Transactions
Data
Definition
Language
Host
Operating
System U S E R
Transactions
User
Programs
Data
Manipulation
Language
Transactions
User
Programs
Query
Language
Physical
Database
User Queries 8

10. DBMS Features
User Programs - makes the presence of the DBMS transparent to the user
Direct Query - allows authorized users to access data without programming
Application Development - user created applications
Backup and Recovery - copies database
Database Usage Reporting - captures statistics on database usage (who, when, etc.)
Database Access - authorizes access to sections of the database 10

11. Internal Controls and DBMS
The purpose of the DBMS is to provide controlled access to the database.
The DBMS is a special software system programmed to know which data elements each user is authorized to access and deny unauthorized requests of data. 7

12. Data Definition Language (DDL)
DDL is a programming language used to define the database to the DBMS.
The DDL identifies the names and the relationship of all data elements, records, and files that constitute the database.
Viewing Levels:
internal view - physical arrangement of records (1)
conceptual view - representation of database (1)
user view - the portion of the database each user views (many) 11

13. Data Manipulation Language (DML)
DML is the proprietary programming language that a particular DBMS uses to retrieve, process, and store data.
Entire user programs may be written in the DML, or selected DML commands can be inserted into universal programs, such as COBOL and FORTRAN. 12

14. Query Language
The query capability permits end users and professional programmers to access data in the database without the need for conventional programs.
ANSI’s Structured Query Language (SQL) is a fourth-generation language that has emerged as the standard query language. 13

15. Functions of the DBA

16. Logical Data Structures
A particular method used to organize records in a database is called the database’s structure.
The objective is to develop this structure efficiently so that data can be accessed quickly and easily.
Four types of structures are:
hierarchical (aka the tree structure)
network
relational
object-oriented

17. The Relational Model
The relational model portrays data in the form of two dimensional tables:
relation - the database table
attributes (data elements) - form columns
tuples (records) - form rows
data - the intersection of rows and columns 31

18. PROJECT - filtering out columns, such as the green
RESTRICT - filtering out rows,
such as the yellow
JOIN X1 Y1 Z1 X1 Y1 Y1 Z1 X2 Y2 Y2 Z2 X2 Y2 Z2 X3 Y1 Y3 Z3 X3 Y1 Z1 35

19. Properly Designed Relational Tables
No repeating values - All occurrences at the intersection of a row and column are a single value.
The attribute values in any column must all be of the same class.
Each column in a given table must be uniquely named.
Each row in the table must be unique in at least one attribute, which is the primary key. 32

20. Crow’s Feet Cardinalities
(1:0,1)
(1:1)
(1:0,M)
(1:M)
(M:M) 23

21. Relational Model Data Linkages (>1 table)
No explicit pointers are present. The data are viewed as a collection of independent tables.
Relations are formed by an attribute that is common to both tables in the relation.
Assignment of foreign keys:
if 1 to 1 association, either of the table’s primary key may be the foreign key.
if 1 to many association, the primary key on one of the sides is embedded as the foreign key on the other side.
if many to many association, may embed foreign keys or create a separate linking table. 33

22. Three Types of Anomalies
Insertion Anomaly: A new item cannot be added to the table until at least one entity uses a particular attribute item.
Deletion Anomaly: If an attribute item used by only one entity is deleted, all information about that attribute item is lost.
Update Anomaly: A modification on an attribute must be made in each of the rows in which the attribute appears.
Anomalies can be corrected by creating relational tables. 79

23. Advantages of Relational Tables
Removes all three anomalies
Various items of interest (customers, inventory, sales) are stored in separate tables.
Space is used efficiently.
Very flexible. Users can form ad hoc relationships. 38

24. The Normalization Process
A process which systematically splits unnormalized complex tables into smaller tables that meet two conditions:
all nonkey (secondary) attributes in the table are dependent on the primary key
all nonkey attributes are independent of the other nonkey attributes
When unnormalized tables are split and reduced to third normal form, they must then be linked together by foreign keys. 38

25. Steps in Normalization
Table with
repeating groups
Remove
repeating
groups
First normal
form 1NF
Remove
partial
dependencies
Second normal
form 2NF
Remove
transitive
dependencies
Third normal
form 3NF
Remove
remaining
anomalies
Higher normal
forms 86

26. Accountants and Data Normalization
The update anomaly can generate conflicting and obsolete database values.
The insertion anomaly can result in unrecorded transactions and incomplete audit trails.
The deletion anomaly can cause the loss of accounting records and the destruction of audit trails.
Accountants should have an understanding of the data normalization process and be able to determine whether a database is properly normalized. 40

27. Six Phases in Designing Relational Databases
Identify entities
identify the primary entities of the organization
construct a data model of their relationships
Construct a data model showing entity associations
determine the associations between entities
model associations into an ER diagram

28. Six Phases in Designing Relational Databases
Add primary keys and attributes to the model
assign primary keys to all entities in the model to uniquely identify records
every attribute should appear in one or more user views
Normalize the data model and add foreign keys
remove repeating groups, partial and transitive dependencies
assign foreign keys to be able to link tables

29. Six Phases in Designing Relational Databases
Construct the physical database
create physical tables
populate tables with data
Prepare the user views
normalized tables should support all required views of system users
user views restrict users from have access to unauthorized data

30. Central Site Site A Site B Site C Centralized Database
Distributed Data
Processing
Centralized
Database
Central
Site
Site A
Site B
Site C 23

31. Distributed Data Processing
DP is organized around several information processing units (IPUs) distributed throughout the organization and placed under the control of the end users.
DDP does not mean decentralization
IPUs are connected to one another and coordinated
Decentralization does not attempt to integrate the parts into a logical whole unit.

32. Potential Advantages of DDP
Cost reductions in hardware and data entry tasks
Improved cost control responsibility
Improved user satisfaction since control is closer to the user level
Backup of data can be improved through the use of multiple data storage sites

33. Potential Disadvantages of DDP
Loss of control
Mismanagement of organization-wide resources
Hardware and software incompatibility
Redundant tasks and data
Consolidating incompatible tasks
Difficulty attracting qualified personnel
Lack of standards

34. Centralized Databases in DDP Environment
The data is retained in a central location.
Remote IPUs send requests for data.
Central site services the needs of the remote IPUs.
The actual processing of the data is performed at the remote IPU.

35. Data Currency Occurs in DDP with a centralized database
During transaction processing, the data will temporarily be inconsistent as a record is being read and updated.
Database lockout procedures are necessary to keep IPUs from reading inconsistent data and from writing over a transaction being written by another IPU.

36. Distributed Databases: Partitioning
Splits the 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
the volume of transmitted data between IPUs is reduced
reduces the potential data loss from a disaster

37. The Deadlock Phenomenon
Especially a problem with partitioned databases
Occurs when multiple sites lock each other out of data that they are currently using
One site needs data locked by another site.
Special software is needed to analyze and resolve conflicts.
Transactions may be terminated and have to be restarted.

38. The Deadlock Phenomenon
Locked A, waiting for C
Locked E, waiting for A
A,B
E, F
C,D
Locked C, waiting for E

39. Distributed Databases: Replication
The duplication of the entire database for multiple IPUs
This method is effective for situations with a high degree of data sharing, but no primary user, and supports read-only queries.
The data traffic between sites is reduced considerably.

40. Concurrency Problems and Control Issues
Database concurrency is the presence of complete and accurate data at all IPU sites. With replicated databases, maintaining current data at all locations is a difficult task.
Time stamping may be used to serialize transactions and to prevent and resolve any potential conflicts created by updating data at various IPUs.