Transcript McLeod_CH08

Management
Information Systems,
10/e
Raymond McLeod Jr. and George P. Schell
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
1
Chapter 8
Information in Action
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
2
Learning Objectives
►
►
►
►
►
Know that a firm’s ability to develop effective information
systems can be a key factor in its success.
Recognize that the transaction processing system
processes describes the firm’s basic daily operations.
Be familiar with the processes performed by a transaction
processing system for a distribution firm.
Recognize that organizational information systems have
been developed for business areas and organizational
levels.
Be familiar with architectures of marketing, human
resources, manufacturing, and financial information
systems.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
3
Learning Objectives (Cont’d)
Know the architecture of an executive information system.
► Understand what customer relationship management is
and why it requires a large computer storage capability.
► Recognize how a data warehouse differs from a database.
► Understand the architecture of a data warehouse system.
► Know how data are stored in a data warehouse data
repository.
► Know how a user navigates through the data repository.
► Know what on-line analytical processing (OLAP) is.
► Know the two basic ways to engage in data mining.
►
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
4
Information as a Critical Success
Factor
► Critical
success factor (CSF) was coined by
Ronald Daniel to identify a few key activities that
spell success or failure for any type of
organization.
► Transaction processing system (TPS) is the
information system that gathers data describing
the firm’s activities, transforms the data into
information, and makes the information available
to users both inside and outside the firm.
 1st business application to be installed on computers.
► Also
electronic data processing (EDP) system and
accounting information system.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
5
Figure 8.1 A Model of a Transaction
Processing System
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
6
System Overview
► Distribution
system is a TPS used by
distribution firms.
► Distribution firms distribute products or
services to their customers.
► We will use data flow diagrams, or DFDs, to
document the system.
► Figure 8.2 represents the highest level.
► Figure 8.3 identifies the three major
subsystems.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
7
Figure 8.2 A Context Diagram of
Distribution System
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
8
Figure 8.3 A Figure 0 Diagram of the
Distribution System
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
9
Major Subsystems of Distribution
System
► Systems
that fill customer orders.
► Systems
that order replenishment stock.
 Order entry system enters customer orders into the
system.
 Inventory system maintains the inventory records.
 Billing system prepares the customer invoices.
 Accounts receivable system collects the money from
the customers.
 Purchasing system issues purchase orders to
suppliers for needed stock.
 Receiving system receives the stock.
 Accounts payable system makes payments.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
10
Figure 8.4 A Figure 1 Diagram of the
System that Fills Customers Orders
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
11
Figure 8.5 A Figure 2 Diagram of
Systems That Order Replenishment
Stock
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
12
Major Subsystems of Distribution
System (Cont’d)
► Systems
that perform general ledger processes.
 General ledger system is the accounting system that
combines data from other accounting systems for the
purpose of presenting a composite financial picture of
the firm’s operations.
 General ledger is the file that contains the combined
accounting data.
 Updated general ledger system posts records that
describe various actions and transactions to the general
ledger.
 Prepare management reports system uses the
contents of the general ledger to prepare the balance
sheet, income statement, and other reports.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
13
Figure 8.6 A Figure 3 Diagram of the Systems
that Perform General Ledger Processes
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
14
Organizational Information Systems
► Organizational
information systems are
developed to meet the needs for
information relating to those particular parts
of the organization.
► Marketing information system (MKIS)
provides information that relates to the
firm’s marketing activities.
 Consists of a combination of input and output
subsystems connected by a database.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
15
Figure 8.7 A Model of Marketing
Information System
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
16
Marketing Information System
►
►
Output subsystems provide information about critical
elements in marketing mix.
Marketing mix consists of four main ingredients that
management manages in order to meet customers’ needs
at a profit.
 Product subsystem provides information about the firm’s
products.
 Place subsystem provides information about the firm’s
distribution network.
 Promotion subsystem provides information about the firm’s
advertising and personal selling activities.
 Price subsystem helps the manager make pricing decisions.
 Integrated-mix subsystem enables the manager to develop
strategies that consider the combined effects of the ingredients.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
17
Marketing Information System
(Cont’d)
► Database
is populated with data from the three
MKIS input subsystems.
► Input
subsystems
 Transaction processing system gathers data from
both internal and environmental sources and enters the
data into the database.
 Marketing research subsystem gathers internal and
environmental data by conducting special studies.
 Marketing intelligence subsystem gathers
environmental data that serves to keep management
informed of activities of the firm’s competitors and
customers and other elements that can influence
marketing operations.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
18
Other Organizational Information
System
► Human
Resources information system
(HRIS) provides information to managers
throughout the firm concerning the firm’s human
resources.
► Manufacturing information system provides
information to managers throughout the firm
concerning the firm’s manufacturing operations.
► Financial information system provides
information to managers throughout the firm
concerning the firm’s financial activities.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
19
Figure 8.8 A Model of a Human
Resource Information System
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
20
Figure 8.9 A Model of Manufacturing
Information System
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
21
Figure 8.10 A Model of Financial
Information System
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
22
The Executive Information System
► Executive
information system (EIS) is a
system that provides information to upper-level
managers on the overall performance of the firm;
also called Executive support system (ESS).
► Drill-down capability allows for executives to
bring up a summary display and then successively
display lower levels of detail until executives are
satisfied that they have obtained as much detail as
is necessary.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
23
Figure 8.11 An Executive Information
System Model
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
24
Figure 8.12 Drill-Down Technique
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
25
Customer Relationship Management
► Customer
relationship management (CRM) is
the management of the relationships between the
firm and its customers so that both the firm and
its customers receive maximum value from the
relationship.
► CRM system accumulates customer data over a
long term–5 years, 10 years, or more-and uses
that data to produce information for users.
 Uses a data warehouse.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
26
Data Warehousing
► Data
warehouse describes data storage that has
the following characteristics:
 Storage capacity is very large.
 Data are accumulated by adding new records, as
opposed to being kept current by updating existing
records with new information.
 Date are easily retrievable.
 Date are used solely for decision making, not for use in
the firm’s daily operations.
► Data
mart is a database that contains data
describing only a segment of the firm’s operations.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
27
The Data Warehousing System
► Data
warehousing is the creation and use
of a data warehouse or data mart.
► Primary data sources are TPS and data
obtained from other sources, both internal
and environmental; any data identified as
having potential value in decision making.
► Staging area is where the data undergoes
extraction, transformation, and loading
(abbreviated as ETL process)
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
28
Data Warehousing System (Cont’d)
► Extraction
process combines data from the various
sources.
► Transformation process cleans the data, puts it into
standardized format, and prepares summaries.
 Data stored in both detail and summary form.
► Loading
process involves the entry of the data into
the data warehouse repository.
► Metadata
 “Data about data”
 Data that describes the data in the data repository
 Tracks data as it flows through the data warehouse system
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
29
Figure 8.13 A Model of a Data
Warehousing System
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
30
Storing Data in the Warehouse Data
Repository
► Dimension
tables store the identifying and
descriptive data.
 Dimension provides the basis for viewing the data
from various perspectives or dimensions.
► Fact
tables are separate tables containing the
quantitative measures of an entity.
 Combined with dimension table data, various analyses
can be prepared.
 Users can request information that involves any
combination of the dimensions and facts.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
31
Figure 8.14 A Sample Dimension
Table
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
32
Figure 8.15 A Sample Fact Table
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
33
Storing Data … (Cont’d)
► Information
package identifies all of the
dimensions that will be used in analyzing a
particular activity.
► Star schema-for each dimension, a key identifies
the dimension and provides the link to the
information package that results in a structure that
is similar to the pattern of a star.
 The warehouse data repository contains multiple star
schemas, one for each type of activity to be analyzed.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
34
Figure 8.16 Information Package
Format
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
35
Figure 8.17 A Sample Information
Package
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
36
Figure 8.18 Star Schema Format
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
37
Figure 8.19 A Sample Star Schema
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
38
Information Delivery
► Drill
down-the process of navigating down
through the levels of detail.
► Roll up-enables the user to begin with a detail
display and then summarizes the details into
increasingly higher summary levels.
► Drill across-moving from one data hierarchy to
another.
► Drill through-going from a summary level to the
lowest level of detail.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
39
Figure 8.20 Navigating Through the
Warehouse Data Repository
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
40
Figure 8.21 Drilling Across
Hierarchies Produces Multiple Views
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
41
OLAP
►
►
On-line analytical processing (OLAP) enables the user
to communicate with the data warehouse either through a
GUI or a Web interface and quickly produce information in
a variety of forms, including graphics.
Relational OLAP (ROLAP) uses a standard relational
database management system.
 ROLAP data exists in detailed form.
 Analyses must be performed to produce summaries.
 Constrained to a limited number of dimensions.
►
Multidimensional OLAP (MOLAP) uses a special
multidimensional database management system.
 MOLAP data are preprocessed to produce summaries at the various
levels of detail and arranged by the various dimensions.
 Faster summary ability, can use many dimensions–10 or more.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
42
Figure 8.22 ROLAP and MOLAP
Architectures
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
43
Figure 8.23 An Example of a Report
than Could Be Produced with ROLAP
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
44
Figure 8.24 An Example of a Report
that Could Be Produced with MOLAP
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
45
Data Mining
► Data
mining is the process of finding
relationships in data that are unknown to the user.
► Hypothesis verification begins with the user’s
hypothesis of how data are related.
 Retrieval process guided entirely by user.
 Selected information can be no better than user’s
understanding of the data.
 Traditional way to query a database.
► Knowledge
discovery is when the data
warehousing system analyzes the warehouse data
repository, looking for groups with common
characteristics.
© 2007 by Prentice Hall
Management Information Systems, 10/e
Raymond McLeod and George Schell
46