Download ch13 - AIS sem 1 2011

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
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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
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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
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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
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SO 1 The need for data collection and storage
Storing and Accessing Data
Data Storage Terminology
Chapter
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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
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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
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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
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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
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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
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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
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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
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 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
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Accessing customers’ payment histories.
d. determining customers’ behavior patterns.
Chapter
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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
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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
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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. Flat file database.
c.
Distributed database.
d. High-impact process.
Chapter
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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

Chapter
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Control techniques such as

data validation,

control totals and reconciliation, and

reports that are analyzed by managers.
SO 9 Controls for data and databases
Copyright
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use of these programs or from the use of the information
contained herein.
Chapter
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