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DATABAS
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SYSTEMS
Chapter
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objectives
After studying this chapter, you should:Double-click on it
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Understand the operational problems inherent in the flat-file approach to data
management that gave rise to the database approach
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Understand the relationships among the fundamental components of the database
concept
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Recognize the defining characteristics of three database models: hierarchical,
network, and relational
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Understand the operational features and associated risks of deploying centralized,
partitioned, and replicated database models in the DDP environment
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Be familiar with the audit objectives and procedures used to test data
management
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Data
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DATA MANAGEMENT
APPROACH
FLAT-FILE APPROACH
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It is most often associated with so-called LEGACY
SYSTEMS. The flat-file environment promotes a single-user view
approach to data management whereby end users own their data
files rather than share them with other users. Data files are
therefore structured, formatted, and arranged to suit the specific
needs of the owner or primary user of the data.
● Data redundancy
Replication of essentially the same data in multiple
files.
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Data
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Data
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THREE SIGNIFICANT
PROBLEMS IN THE FLAT-FILE
ENVIRONMENT
Data storage
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Data Updating
Currency of information
Task-Data dependency
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Data
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DATA MANAGEMENT
APPROACH
THE DATABASE APPROACH
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Access to the data resource is controlled by a database
management system. THE DBMS is a special software system that is
programmed to know which data elements each user is authorized to
access. This approach centralizes the organization's data into a common
database that is shared by the user community.
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Data
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KEY ELEMENTS OF THE
DATABASE ENVIRONMENT
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DBMS
USERS
DATABASE ADMINISTRATOR (DBA)
PHYSICAL DATABASE
Data
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Database Management System
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Typical Features
PROGRAM DEVELOPMENT - The DBMS contains application software.
Both programmers and end users may employ this feature to create
applications to access the database.
1.
BACKUP and RECOVERY - During processing, the DBMS periodically
makes backup copies of the physical database.
2.
DATABASE USAGE REPORTING - This feature captures statistics on what
data are being used, when they are used, and who uses them.
3.
DATABASE ACCESS - The most important feature of a DBMS is to permit
authorized user access, both formal and informal to the database.
4.
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THREE SOFTWARE MODULES
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DATA DEFINITION LANGUAGE
is a programming language used to define the database to the
DBMS.
3 LEVELS
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Physical view/internal view
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Conceptual view/logical view (schema)
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External view/user view (subschema)
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THREE SOFTWARE MODULES
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DATA MANIPULATION LANGUAGE
is the proprietary programming language that a
particular DBMS uses to retrieve, process, and store data.
Selected DML commands can be inserted into programs that are
written in universal languages such as COBOL & FORTRAN.
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THREE SOFTWARE MODULES
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QUERY LANGUAGE
The second method of database access is the informal
method of queries. This feature allows authorized users to
process data independent of professional programmers by
providing a "friendly" environment for integrating and retrieving
data to produce query reports.
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DBMS OPERATION
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DATABASE ADMINISTRATOR
The DBA is responsible for managing the
database resource. The sharing of a common database
by multiple users requires organization, cooperation,
rules and guidelines to protect the integrity of
database.
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FUNCTIONS OF THE
DATABASE
ADMINISTRATOR
Database Planning:
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Develop organization's database strategy
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Define database environment
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Define data requirements
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Develop data dictionary
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FUNCTIONS OF THE
DATABASE
ADMINISTRATOR
Design:
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Schema
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Subschema
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Internal view of databases
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DB controls
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FUNCTIONS OF THE
DATABASE
ADMINISTRATOR
Implementation:
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Determine access policy
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Implement security controls
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Specify tests procedures
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Establish programming standards
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FUNCTIONS OF THE
DATABASE
ADMINISTRATOR
Operation and Management:
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Evaluate database performance
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Recognize database as user needs demand
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Review standards and procedures
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FUNCTIONS OF THE
DATABASE
ADMINISTRATOR
Change and Growth:
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Plan for change and Growth
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Evaluate new technology
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ORGANIZATIONAL
INTERACTIONS OF THE DBA
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Typical File Processing
Retrieve a record from the file based on its primary key value.
Operations
1.
2.
Insert a record into a file.
3.
Update a record in the file.
4.
Read a complete file of records.
5.
Find the next record in a file.
6.
Scan a file for records with common secondary keys.
7.
Delete a record from a file.
Data
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Data
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Data Structures
Data structures are the bricks and mortar of the database. The
data structures allows records to be located, stored, and retrieved,
and enables movement from one record to another.
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Two fundamental components
Organization
Access method
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Data
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Data Organization
The organization of a file refers to the way records are
physically arranged on the storage device. This may be either
sequential or random.
Data Access Methods
Access methods are computer program that are part of the
operating system and are used to locate records and to navigate
through the database.
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1.
2.
3.
4.
5.
6.
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The criteria that influence the selection of the data
structure include:
Rapid file access and data retrieval
Efficient use of disk storage space
High throughput for transaction processing
Protection from data loss
Ease of recovery from system failure
Accommodation of file growth
Data
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Data
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DBMS Models
A data model is an abstract representation of the data about entities
of interest. These include resources (asset), events (transactions), and agents
(personnel or customers, etc.) and their relationships in an organization. The
purpose of a data model is to represent entities and defining their attributes in a
way that is understandable to users.
Three common models are the hierarchical, the network, and the
relational models. Because of certain conceptual similarities, we shall examine
the hierarchical and network models first. These are termed navigational
models because of explicit links or paths among their data elements.
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Data
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Database Terminology

Entity and Record Type. An entity is anything about which the organization wishes to
capture data. A Record Type is a physical database representation of an entity . Database
designers group together into tables (files) the record types that pertain to specific
entities.

Occurrence. The term occurrence relates to the number of records of represented by a
particular record type.
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Attributes. Entities are defined by attributes
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Database. A database is the set of record types that an organization needs to support its
business processes.
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Associations. Record types that constitute a database exist in relation to other record
types. This is called an association.
Three basic associations are one-to-one, one-to-many, and many-to-many.
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Data
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The Hierarchical Model
The earliest DBAs were based on the hierarchical data model. This was a
popular method of data presentation because it reflected, more or less accurately,
many aspects of an organization that are hierarchical in relationship. IBM's
information management system (IMS) is the most prevalent example of a
hierarchical database. It was introduced in 1968 and is still a popular database
model over 40 years later.
The hierarchical model is constructed of sets that describe the relationship
between two linked files. Each set contains a parent and a child. Files at the same
level with the same parent are called siblings. This structure is also called a tree
structure. The highest level in the tree is the root segment, and the lowest file in a
particular branch is called a leaf.
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Data
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Navigational Databases
The hierarchical data model is called
navigational database because traversing the files
requires following a predefined path.
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DATA INTEGRATION IN A
HIERARCHICAL DATABASE
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Data
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Limitations of the Hierarchical
Model
The hierarchical model presents an artificially constrained view
of data relationships. Based on the proposition that all business
relationships are hierarchical (or can be represented as such) this model
does not always reflect reality. The following rules, which govern the
hierarchical model, reveal it operating constraints:
1.
A parent record may have one or more child records.
2.
No child record can have more than one parent.
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Data
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The Network Model
In the late 1970s, an ANSI committee created the Committee
on Development of Applied Symbol Languages (CODASYL), which formed
database task group to develop standards for database design. CODASYL
developed the network model for databases. The most popular example
of the network model is integrated database management system
(IDMS), which Cullinane/Cullinet Software introduced into the
commercial market in the 1980s.
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Data
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TheE. F.Relational
Model
Codd originally proposed the principles of the relational model in the late 1960s.
The formal model has its foundation in relational algebra and set theory, which provide the
theoretical basis for most of the data manipulation operations used.
The relational model portrays data in the form of two-dimensional tables.
Properly designed tables posses the following four characteristics:
All occurrences at the intersection of a row and a column are a single value. No multiple values
(repeating groups) are allowed.
1.
2.
The attribute values in any column must all be of the same class.
3.
Each column in a given table must be uniquely named.
4.
Each row in the table must be unique in at least one attribute. This attribute is the primary key.
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DATABASE in a distributed
environment
Two Basic Options:
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Centralized Databases
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Distributed Databases
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DATABASE in a distributed
environment
Centralized Databases
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The first approach involves retaining the data in
a central location. Remote IT units send request for
data to the central site, which processes the request
and transmits the data back to the requesting IT unit.
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Data currency in a ddp
During data processing, account balances pass through a
environment
state of temporary inconsistency where their values are
incorrectly stated.
To achieve data currency, simultaneous access to
individual data elements by multiple IT units must be prevented.
The solution to this problem is to employ a database lockout,
which is software control (usually a function of the DBMS) that
prevents multiple simultaneous accesses to data.
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DATABASE in a distributed
environment
Distributed Databases
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Distributed databases fall into two categories:
partitioned databases or replicated databases.
This section examines issues, features, and trade-offs
that need to be evaluated in deciding the disposition of
the databases.
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distributed databases
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Partitioned databases
The partitioned database approach splits the central database into segments or
partitions that are distributed to their primary users.
The advantages of this approach:
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Having data stored at local sites increases users' control
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Transaction processing response time is improved by permitting local access to data
and reducing the volume of data that must be transmitted between IT units.
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Partitioned databases can reduce the potential effects of a disaster. By locating data at
several sites, the loss of a single IT unit does not eliminate all data processing by the
organization.
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The Deadlock Phenomenon
In a distributed environment, it is possible for
multiple sites to lock out each other from the database,
thus preventing each from processing its transactions.
A deadlock is a permanent condition that must
be resolved by special software that analyzes each
deadlock condition to determine the best solution.
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Deadlock Resolution
Resolving a deadlock usually involves terminating one or more
transactions to complete processing of the other transactions in the
deadlock.
Some of the factors that are considered in this decision follow:
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The resources currently invested in the transaction.
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The transaction's stage of completion.
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The number of deadlocks associated with the transaction.
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Replicated Databases
Replicated databases are effective in companies
where there exists a high degree of data sharing but no
primary use. Since common data are replicated at each
IT unit site, the data traffic between sites is reduced
considerably.
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Concurrency Control
Database concurrency is the presence of
complete and accurate data at all user sites. System
designers need to employ methods to ensure that
transactions processed at each site are accurately
reflected in the databases of all the other sites.
A commonly used method for concurrency
control is to serialize transactions.
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Database Distribution Methods and
the Accountant
The decision to distribute databases is one that should be entered into thoughtfully.
There are many issues and trade-offs to consider. Here are some of the most basic
questions to be addressed.
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Should the organization's data be centralized or distributed?
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If data distribution is desirable, should the databases be replicated or partitioned?
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If replicated, should the databases be totally replicated or partially replicated?
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If the database is to be partitioned, how should the data segments be allocated
among the sites?
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CONTROLLING AND AUDITING DATA
Controls
over data management SYSTEMS
systems fall into two categories: Access
MANAGEMENT
Controls and Backup Controls.
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ACCESS CONTROLS
In the shared database environment, access control risks include corruption,
theft, mis use, and destruction of data. These threats originate from both unauthorized
intruder and authorized users who exceed their access privileges.

User Views
The user view or subschema is a subset of the total database that
defines the user's data domain and provides access to the database.
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Inference Controls
One advantage of the database query capability is
that it provides users with summary and statistical data
for decision making. To preserve the confidentiality and
integrity of the database, inference controls should be in
place to prevent users from inferring, through query
features, specific data values that they are unauthorized
to access.
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Inference controls attempt to prevent three types of compromises
to the database:
1.
Positive compromise - the user determines the specific value of
a data item.
2.
Negative compromise - the user determines that a data item
does not have a specific value.
3.
Approximate compromise - the user is unable to determine the
exact value of an item but is able to estimate it with sufficient
accuracy to violate the confidentiality of the data.
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Audit Procedures for Testing
Database Access Controls
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Responsibility for authority tables and subschemas
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Appropriate Access Authority
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Biometric Controls
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Inference Controls
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Encryption Controls
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Backup Controls
Data can be corrupted and destroyed by
malicious acts from external hackers, disgruntled
employees, disk failure, program errors, fires, floods and
earthquakes. To recover from such disasters,
organizations must implement policies, procedures and
techniques that systematically and routinely provide
backup copies of critical files.
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Audit Objective Relating to Flat-File Backup
Verify that backup controls in place are effective
in protecting data files from physical damage.

Audit Procedures for Testing Flat-File Backup
Controls
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Sequential file backup
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Backup Transaction files
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Off-Site Storage
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Backup
The backup features makes a periodic backup of the entire
database. This is an automatic procedure that should be performed
at least once a day.

Transaction Log (Journal)
Provides an audit trial of all processed transactions. It lists
transactions in a transaction log file and records the resulting
changes to the database in a separate database change log.
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Checkpoint Feature
The suspends all data processing while the
system reconciles the transaction log and the database
change log against the database.
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Recovery Module
Uses the logs and backup files to restart the
system after a failure.
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Audit Objective Relating to Database Backup
Verify that controls over the data resource are sufficient to
preserve the integrity and physical security of the database.

Audit Procedures for Testing Database Backup Controls
The auditor should verify that backup is performed
routinely and frequently to facilitate the recovery of lost, destroyed
or corrupted data without excessive reprocessing
The auditor should verify that automatic backup procedures
are in place and functioning and that copies of the database are
stored off-site for further security
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Chapter 4
Thank you
for listening
GROUP 4
MONTOYA, ALEISSA GRACE
SACMAN, CARMELA
SORIANO, VANESSA
SY, ANGELIKA JOYCE