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Chapter
13-1
Data and
Databases
Chapter
13-2
Accounting Information Systems, 1st Edition
Study Objectives
1.
The need for data collection and storage
2.
Methods of storing data and the interrelationship between storage
and processing
3.
The differences between batch processing and real-time processing
4.
The importance of databases and the historical progression from
flat-file databases to relational databases
5.
The need for normalization of data in a relational database
6.
Data warehouse and the use of a data warehouse to analyze data
7.
The use of OLAP and data mining as analysis tools
8.
Distributed databases and advantages of the use of distributed data
9.
Controls for Data and Databases
10.
Ethical issues related to data collection and storage, and their use in
IT systems
Chapter
13-3
The Need for Data Collection and Storage
Data are the set of facts collected from transactions,
whereas information is the interpretation of data that
have been processed.
Main reasons to store transaction data:
1.
To complete transactions from beginning to end.
2. To follow up with customers or vendors and to expedite
future transactions.
3. To create accounting reports and financial statements.
4. To provide feedback to management.
Chapter
13-4
SO 1 The need for data collection and storage
The Need for Data Collection and Storage
Typical storage and processing techniques:
1. The storage media types for data: sequential and
random access
2. Methods of processing data: batch and real time
3. Databases and relational databases
4. Data warehouses, data mining, and OLAP
5. Distributed data processing and distributed
databases
Chapter
13-5
SO 1 The need for data collection and storage
The Need for Data Collection and Storage
Concept Check
Which of the following best describes the relationship
between data and information?
a. Data is interpreted information.
b. Information is interpreted data.
c. Data is more useful than information in decision
making.
d. Data and information are not related.
Chapter
13-6
SO 1 The need for data collection and storage
Storing and Accessing Data
Data Storage Terminology
Chapter
13-7
Character
Record
Field
File
Exhibit 13-1
Data Hierarchy
Database
SO 2 Methods of storing data and the interrelationship
between storage and processing
Storing and Accessing Data
Data Storage Media
Magnetic tape
Sequential access
Random Access
Chapter
13-8
Early Days of
Mainframe
Computers
Modern IT
Systems
SO 2 Methods of storing data and the interrelationship
between storage and processing
Storing and Accessing Data
Concept Check
A character is to a field as
a. Water is to a pool.
b. A pool is to a swimmer.
c. A pool is to water.
d. A glass is to water.
Chapter
13-9
SO 2 Methods of storing data and the interrelationship
between storage and processing
Storing and Accessing Data
Concept Check
Magnetic tape is a form of
a. Direct access media.
b. Random access media.
c. Sequential access media.
d. Alphabetical access media.
Chapter
13-10
SO 2 Methods of storing data and the interrelationship
between storage and processing
Data Processing Techniques
Batch Processing
Real-time
Processing
Exhibit 13-2
Comparison of Batch and
Real-Time Processing
Chapter
13-11
SO 3 The differences between batch processing and real-time processing
Data Processing Techniques
Concept Check
Which of the following is not an advantage of using
real-time data processing?
a. Quick response time to support timely record
keeping and customer satisfaction
b. Efficiency for use with large volumes of data.
c. Provides for random access of data.
d. Improved accuracy due to the immediate
recording of transactions.
Chapter
13-12
SO 3 The differences between batch processing and real-time processing
Databases
Data stored in a form that allows the data to be easily
accessed, retrieved, manipulated, and stored.
Exhibit 13-3
Traditional FileOriented Approach
 Data
redundancy
 Concurrency
Chapter
13-13
SO 4 The importance of databases and the historical progression
from flat-file databases to relational databases
Databases
Exhibit 13-3
Database Approach
Relationships
 One-to-One
Database Management System (DBMS) is
software that manages the database and
controls the access and use of data by
individual users and applications.
Chapter
13-14
 One-to-Many
 Many-to-Many
SO 4 The importance of databases and the historical progression
from flat-file databases to relational databases
The History of Databases
Exhibit 13-4
Database Table
Flat File Database Model

1950s and 1960s

Text format, sequential order

Sequential processing
Chapter
13-15

Large volumes of similar
transactions

Single record not easily
retrieved or stored
SO 4 The importance of databases and the historical progression
from flat-file databases to relational databases
The History of Databases
Hierarchical Database Model
 Inverted tree structure
 Parent–child, represent one-to-many relationships
 Record pointer
Chapter
13-16
Exhibit 13-5
Linkages in a
Hierarchical Database
SO 4 The importance of databases and the historical progression
from flat-file databases to relational databases
The History of Databases
Network Database Model
 Inverted tree structure
 More complex relationship linkages by use of
shared branches
 Not very popular, rarely used
Chapter
13-17
SO 4 The importance of databases and the historical progression
from flat-file databases to relational databases
The History of Databases
Relational Database Model
 Developed in 1969
 Stores data in two-dimensional tables
 Most widely used database structure today
 Examples include; IBM DB2, Oracle Database, and
Microsoft Access
Chapter
13-18
SO 4 The importance of databases and the historical progression
from flat-file databases to relational databases
Databases
Concept Check
If a company stores data in separate files in its
different departmental locations and is able to update
all files simultaneously, it would not have problems with
a. attributes.
b. data redundancy.
c. industrial espionage.
d. concurrency.
Chapter
13-19
SO 4 The importance of databases and the historical progression
from flat-file databases to relational databases
Databases
Concept Check
When the data contained in a database are stored in
large, two-dimensional tables, the database is referred
to as a
a. flat file database.
b. hierarchical database.
c. network database.
d. relational database.
Chapter
13-20
SO 4 The importance of databases and the historical progression
from flat-file databases to relational databases
Databases
Concept Check
Database management systems are categorized by the
data structures they support. In which type of
database management system is the data arranged in a
series of tables?
a. Network.
b. Hierarchical.
c. Relational.
d. Sequential.
Chapter
13-21
SO 4 The importance of databases and the historical progression
from flat-file databases to relational databases
The Need for Normalized Data
Relational databases consist of several small tables.
Small tables can be joined in ways that represent
relationships among the data.
Exhibit 13-6
Relational Database in
Microsoft Access
Bolded field is
the primary key.
Chapter
13-22
SO 5 The need for normalization of data in a relational database
The Need for Normalized Data
Relational database has flexibility in
retrieving data. Structured query
language (SQL) has become the
industry standard.
SELECT Customers.CustomerID, Customers.CompanyName,
Orders.OrderID, Orders.ShippedDate FROM Customers INNER
JOIN Orders ON Customers.CustomerID Orders.CustomerID;
Chapter
13-23
Exhibit 13-7
Relational Database in
Microsoft Access
SO 5 The need for normalization of data in a relational database
The Need for Normalized Data
The process of converting data into tables that meet the
definition of a relational database is called data
normalization.
 Seven rules of data normalization, additive.
 Most relational databases are in third normal form.
 First three rules of data normalization are:
1.
Eliminate repeating groups
2. Eliminate redundant data
3. Eliminate columns not dependent on primary key.
Chapter
13-24
SO 5 The need for normalization of data in a relational database
The Need for Normalized Data
Trade-offs in Database Storage
Relational database
 Not most efficient way to store data that will be
used in other ways.
 Most organizations are willing to accept less
transaction processing efficiency for better query
opportunities.
Chapter
13-25
SO 5 The need for normalization of data in a relational database
The Need for Normalized Data
Concept Check
Which of the following statements is not true with
regard to a relational database?
a. It is flexible and useful for unplanned, ad hoc
queries.
b. It stores data in tables.
c. It stores data in a tree formation.
d. It is maintained on direct access devices.
Chapter
13-26
SO 5 The need for normalization of data in a relational database
Use of a Data Warehouse to Analyze Data
Management often needs data from several fiscal periods
from across the whole organization.
Exhibit 13-8
The Data Warehouse and
Operational Databases
Chapter
13-27
SO 6 Data warehouse and the use of a data warehouse to analyze data
Use of a Data Warehouse to Analyze Data
Management often needs data from several fiscal periods
from across the whole organization.
Build the data warehouse
Identify the data
Standardize the data
Cleanse, or scrub, the data
Upload the data
Chapter
13-28
SO 6 Data warehouse and the use of a data warehouse to analyze data
Use of a Data Warehouse to Analyze Data
Concept Check
A collection of several years’ nonvolatile data used to
support strategic decision-making is a(n)
a. operational database.
b. data warehouse.
c. data mine.
d. what-if simulation.
Chapter
13-29
SO 6 Data warehouse and the use of a data warehouse to analyze data
Data Analysis Tools
Data mining is the process of searching for
identifiable patterns in data that can be used to
predict future behavior.
OLAP is a set of software tools that allow online analysis
of the data within a data warehouse. Analytical methods
in OLAP usually include:
Chapter
13-30
1. Drill down
4. Time series analysis
2. Consolidation
5. Exception reports
3. Pivoting
6. What-if simulations
SO 7 The use of OLAP and data mining as analysis tools
Data Analysis Tools
Concept Check
Data mining would be useful in all of the following
situations except
a.
identifying hidden patterns in customers’ buying habits.
b. assessing customer reactions to new products.
c.
determining customers’ behavior patterns.
d. determining customers’ behavior patterns.
Chapter
13-31
SO 7 The use of OLAP and data mining as analysis tools
Distributed Data Processing
Early days
 Centralized processing
 Centralized databases
Today’s IT Environment
 Distributed data processing (DDP)
 Distributed databases (DDB)
Chapter
13-32
SO 8 Distributed databases and advantages of the use of distributed data
Distributed Data Processing
Distributing the processing and data offers the following
advantages:
1. Reduced hardware cost
2. Improved responsiveness
3. Easier incremental growth
4. Increased user control and user involvement
5. Automatic integrated backup
The most popular type of distributed system is a
client/server system.
Chapter
13-33
SO 8 Distributed databases and advantages of the use of distributed data
Distributed Data Processing
Concept Check
A set of small databases where data are collected,
processed, and stored on multiple computers within a
network is a
a. Centralized database.
b. Distributed database.
c.
Flat file database.
d. High-impact process.
Chapter
13-34
SO 8 Distributed databases and advantages of the use of distributed data
IT Controls for Data and Databases
To ensure integrity (completeness and accuracy) of data
in the database, IT application controls should be used.
These controls are
 input,
 processing, and
 output controls such as
 data validation,
 control totals and reconciliation, and
 reports that are analyzed by managers.
Chapter
13-35
SO 9 Controls for data and databases
Ethical Issues Related to Data Collection
Ethical Responsibilities of the Company
Data collected and stored in databases in many instances
consist of information that is private between the
company and its customer.
Ten privacy practices for online companies:
1.
Chapter
13-36
Management
6. Access
2. Notice
7. Disclosure to third parties
3. Choice and consent
8. Security for privacy
4. Collection
9. Quality
5. Use and retention
10. Monitoring and enforcement
SO 10 Ethical issues related to data collection and
storage, and their use in IT systems
Ethical Issues Related to Data Collection
Ethical Responsibilities of Employees
Employees have an ethical obligation to avoid misuse
of any private or personal data about customers.
There are no specific IT controls that would always
prevent authorized employees from disclosing private
information.
Chapter
13-37
SO 10 Ethical issues related to data collection and
storage, and their use in IT systems
Ethical Issues Related to Data Collection
Ethical Responsibilities of Customers
Customers have an obligation to
 provide accurate and complete information.
 keep any known company information confidential.
 avoid improper use of data that they gain from
accessing a database as a customer.
Chapter
13-38
SO 10 Ethical issues related to data collection and
storage, and their use in IT systems
Ethical Issues Related to Data Collection
Concept Check
Each of the following is an online privacy practice
recommended by the AICPA Trust Principles Privacy
Framework except:
a. Redundant data should be eliminated from the database.
b. Notification of privacy policies should be given to
customers.
c. Private information should not be given to third parties
without the customer’s consent
d. All of the above.
Chapter
13-39
SO 10 Ethical issues related to data collection and
storage, and their use in IT systems
Copyright
Copyright © 2008 John Wiley & Sons, Inc. All rights reserved.
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use of these programs or from the use of the information
contained herein.
Chapter
13-40