Transcript Document 7796806

Logical Models
Describe what a system is or does.
Are independent of technical
implementation.
Depict business requirements.
Are good for communicating with end
users.
Examples: Data, process and object
models.
Data Modeling
A technique for organizing and
documenting a system’s data.
Sometimes called database modeling or
information modeling.
The basic tool for data modeling is called
an entity-relationship diagram (ERD).
Entity Relationship
Diagrams (ERDs)
Three basic elements:
Entity types - the kinds of things the
information system collects information
about.
 Relationship - the way an entity type is
associated with another.
Attributes - specific information about an
entity type.
ERDs

Professor
Professor
Course
Section
Has
Teaches
Has
Is registered in
Office
One-to-one relationship
Section
One-to-many relationship
Section
Optional one-to-many
relationship
Student
Many-to-many relationship
Types of relationships in entity-relationship
Source: Alter S. (1999), Information Systems: A Management Perspective, Third Edition
Entity Relationship Diagram

Offers
Department
Course
Has
Belongs to
Professor
Teaches
Is registered in
Section
Student
Has
Office
Entity - Relationship Diagram for part of a university registration system
Source:
Alter S. (1999), Information Systems: A Management Perspective, Third Edition
Process Modeling
A technique for organizing and
documenting
the structure and flow of data through a
system’s processes and/or
the logic, policies, and procedures to be
implemented by a system’s processes.
(Whitten and Bentley 1998)
Tools: data flow diagrams (DFD) and
IDEF0
Data Flow Diagrams
(DFDs)
Four basic symbols:
Process - transforms inputs into outputs.
Process
External entity - any person or organization
that provides data to a process in the system
or receives data from a process.
External
Entity
Data Flow Diagrams
(DFDs)
Data store - a location where data is
stored.
Data Store
Data flow - represents movement of data
between processes, data stores and
external entities.
Data Flow
Creating DFDs
Starting point is a context diagram, which
verifies the scope of the system by
showing the sources and destinations of
data used and generated by the system.
System represented as a single process is
at the center of the context diagram.
Surrounding that process are external
entities and external data stores.
Creating DFDs (contd.)
The business process in the context
diagram is broken into its constituent
processes to describe exactly how work is
done.
These constituent processes along with
the data stores, external entities and data
flows constitute the top level data flow
diagram.
Creating DFDs (contd.)
Constituent processes can be broken into
sub-processes.
DFDs make it possible to look at business
processes at any level of detail.
In addition to the context diagram, one or
more DFDs are developed based on the
level of detail required.
Purchasing system Context diagram
Order
Supplier
Material
Planning
Department
Material requirement
Payment
PURCHASING
SYSTEM
Invoice
Confirmation of receipt
Receiving
Department
Context diagram for the Ford purchasing system
Source: Alter S. (1999), Information Systems: A Management Perspective, Third Edition
Purchasing System Data Flow Diagram
PCH 1
Material Planning
Department

Material requirement
Purchase order
Order
material
Purchase order
Purchase Orders
Purchase
order details
PCH 2
Decide
what to pay
Invoice
Supplier
Receipt Confirmations
Receipt
details
Receipt
confirmation
Receiving
Department
Payment
authorization
PCH 3
Pay the
supplier
Payment
Data flow diagram showing the main processes in Ford’s original purchasing system
Source: Alter S. (1999), Information Systems: A Management Perspective, Third Edition
Integration Definition for
Function (IDEF)
 Background
 Integrated Computer Aided Manufacturing
(ICAM) program in US Air Force developed the
IDEF series of techniques to improve
manufacturing productivity.
 IDEF0 - Function model, IDEF1 - Information
model, IDEF2 - Dynamic model.
 IDEF techniques widely used in
government/industrial sectors.
IDEF0 Concepts
Technique for performing and managing
needs analysis, benefits analysis,
requirements definition, functional
analysis, and systems design.
Reflects how system functions interrelate
and operate.
IDEF0 Semantics
Box - Function (Ex. Perform Inspection)
Left arrow - Inputs (Ex. Design data)
Top arrow - Controls (Ex. Design requirements)
Bottom arrow - Mechanisms (Ex. Design
Engineer)
Right arrow - Output (Ex. Detailed design)
IDEF0 Semantics (contd.)
Control
Input
FUNCTION
Requirements
Output
Mechanism
Design
data
DESIGN
Engineer
Detailed
design
IDEF0 Diagrams
IDEF0 models composed of: graphic
diagrams, text, and glossary.
Boxes representing a function can be
broken down or decomposed into more
detailed diagrams.
Top level diagram in the model provides
the most general description, with details
provided in the lower levels.
Purchasing System Context diagram
Policies and procedures
Material requirements
Purchase Order
Invoice
Confirmation of receipt
PURCHASING
SYSTEM
Resources
Payment
Purchasing System - IDEF
Diagram
Material
requirements
ORDER
MATERIAL
Purchase order
Receipt details
Invoice
DETERMINE
PAYMENT
Payment authorization
PAY THE
SUPPLIER
Payment
Data Warehouses
Used for building the data management
infrastructure for DSSs and EISs.
A database (or collection of databases)
that is optimized for decision support.
Populated through the extraction and
integration of data from both operational
and external data sources.
Warehouse Architecture
Three types of components
the platform and software (including the
repository) that house the data warehouse,
the data acquisition software or back end,
which extracts data, consolidates and
summarizes the data, and loads the data into
the data warehouse, and
the client or front end software, which allows
users to access and analyze data.
Role of the Repository
Technical role - to support the building
and maintenance of the data warehouse.
document data sources and targets
data transformation and cleanup rules
interface to CASE tools
document warehouse data model
Business-related role - to support end
users in accessing and analyzing data.
Data Marts
Data stores specific to user-communities.
Examples are
EIS server for executives
DSS servers for departments (marketing,
finance, and manufacturing)
Data is structured in the form of a multidimensional database.
Multidimensional Analysis
An analytical technique that allows users
to view data in a dimensional cube format.
Users can perform operations such as drilldown, roll-up, slice and dice, and data
pivoting.
Another term for multidimensional analysis
is on-line analytical processing (OLAP).
Multidimensional Database
Relational structure - data is stored in a
tabular form and is not preprocessed.
Slow performance is an issue.
Star structure - two types of tables are
used, fact and dimension. A “virtual” cube
representation.
Multidimensional database - preprocessed
data stored in the form of arrays.
MOLAP and ROLAP
MOLAP is OLAP with a multidimensional
database.
ROLAP or relational OLAP allows access to
the data without building a specific
multidimensional database.
MOLAP is suited for analysis on data
marts in a multi-user environment.