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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 Student
Section
Section
Office
Is registered in
Has
Has
Teaches
Types of relationships in entity-relationship
Source: Alter S. (1999), Information Systems: A Management Perspective, Third Edition
One-to-one relationship
One-to-many relationship
Optional one-to-many relationship
Many-to-many relationship
Entity Relationship Diagram
Belongs to
Department
StudentSectionProfessor
Course
Office
Offers
Has
TeachesIs registered in
Has
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.
External entity - any person or organization that provides data to a process in the system or receives data from a process.
Process
External Entity
Data Flow Diagrams (DFDs)
Data store - a location where data is stored.
Data flow - represents movement of data between processes, data stores and external entities.
Data Store
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
Invoice
Material
PlanningDepartment
ReceivingDepartment
PURCHASINGSYSTEM
Supplier
Material requirement
Confirmation of receipt
Order
Payment
Context diagram for the Ford purchasing systemSource: Alter S. (1999), Information Systems: A Management Perspective, Third Edition
Purchasing System - Data Flow Diagram
Material requirement
Purchase order
Receipt details
Purchase order details
Material Planning Department
Receiving Department
SupplierPurchase Orders
Receipt Confirmations
Order material
Decide what to pay
Pay the supplier
PCH 1
PCH 2
PCH 3
Purchase order
Invoice
Payment
Receipt confirmation
Data flow diagram showing the main processes in Ford’s original purchasing systemSource: Alter S. (1999), Information Systems: A Management Perspective, Third Edition
Payment authorization
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.)
Input
Mechanism
Control
OutputDesign data
Engineer
Requirements
Detailed design
FUNCTIONDESIGN
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
Material requirements
Confirmation of receipt
Invoice PURCHASING
SYSTEM
Purchase Order
Payment
Policies and procedures
Resources
Purchasing System - IDEF Diagram
ORDERMATERIAL
Material
requirements
Purchase order
DETERMINEPAYMENT
Receipt detailsInvoice
PAY THESUPPLIER
Payment authorization
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
multi-dimensional database.
Multidimensional Analysis
An analytical technique that allows users to view data in a dimensional cube format.
Users can perform operations such as drill-down, 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.