Decision Support Systems Glossary
Decision Support Systems Glossary
Decision Support Systems Glossary
Ad-Hoc Query - Any spontaneous or unplanned question or query. It is a
query that consists of dynamically constructed SQL, which is usually constructed
by desktop-resident query tools.
Ad-Hoc Query Tool - An end-user tool that accepts an English-like or
point-and-click request for data and constructs an ad-hoc query to retrieve the
desired data from a database.
Agents - Self contained processes that run in the background on a
client or server and that perform useful functions for a specific user/owner.
Agents may monitor exceptions based on criteria or execute automated tasks. For
example once an event occurs a daemon performs a pre-defined action and then it
returns to a monitoring state. See daemon.
Aggregate or aggregated Data - Data that is results from applying a
process to combine data elements. Data that is summarized.
Alerts - A notification from an event that a trigger has exceeded a
pre-defined threshold. See agents.
Analytical Hierarchy Process - An approach to decision making that
involves structuring multiple choice criteria into a hierarchy, assessing the
relative importance of these criteria, comparing alternatives for each
criterion, and determining an overall ranking of the alternatives.
Business Data - Data about people, places, things, business rules, and
events used to operate a business. It is not metadata.
Business Intelligence - BI is a popularized, umbrella term introduced
by Howard Dresner of the Gartner Group in 1989 to describe a set of concepts and
methods to improve business decision making by using fact-based support systems.
The term is sometimes used interchangeably with briefing books and executive
information systems. A Business Intelligence System is a DSS.
Business Model - In a data warehouse it is the designer's view of how
the business functions. The view can be from a process, data, event or resource
perspective, and can be the past, present or future state of the business.
Business Transaction - According to Microstrategy, it is a unit of
work acted upon by a data capture system to create, modify, or delete business
data. Each transaction represents a single valued fact describing a single
business event.
Client/server architecture - A network architecture in which computers
on a network act as a server managing files and network services OR as a client
where users run applications and access servers. Clients rely on servers for
resources like web pages, data, files, printing and OLAP. See the client/server
FAQ at
http://www.abs.net/~lloyd/csfaq.txt
Cognitive Overload - A psychological phenomenon characterized by an
overload of information for a decision maker. The amount of information exceeds
the person's cognitive capacity. DSS can reduce or increase cognitive overload.
Communications-Driven DSS - A Decision Support Systems that uses
network and communications technologies to facilitate collaboration and
communication. The communications technologies is central to supporting
decision-making. Technologies include: LANs, WANs, Internet, ISDN, Virtual
Private Networks. Tools used include groupware, Videoconferencing, Bulletin
Boards.
Computer-mediated Communication - The use of computers to create,
store, deliver, and process communications.
Computer Supported Cooperative Work - The use of computers to support
cooperative work among multiple participants (e.g., collaborative authoring), as
distinct from work that may not be cooperative.
Conferencing, Videoconferencing or Teleconferencing - Real-time,
two-way communications. Audio-video telecommunication support of simultaneous
interactions among participants (e.g., involving conference calls or
videoconferencing).
Controllable Variables - Decision variables that can be changed and
manipulated by a decision maker, such as quantity to produce, amount of
resources to allocate, etc. .
Corporate Planning System - A decision support system that holds and
derives knowledge relevant to planning decisions that cut across organizational
units and involve all of an organization's functions (i.e., its operations,
finance, marketing, personnel, etc.).
Critical Success Factors Key areas of business activity in which
favorable results are necessary for a company to reach its goals.
Data - Binary (digital) representations of atomic facts, text,
graphics, bit-mapped images, sound, analog or digital live-video segments. Data
is the raw material of a system supplied by data producers and is used by
information consumers to create information.
Data Conferencing - This term refers to a communication session in
which two or more participants are sharing computer-based data in real-time. Any
participants' keyboard/mouse can control screens of other participants. Voice
communication can be out-of-band using a totally separate voice connection or
in-band using a simultaneous voice and data technology.
Data Dictionary - A database about data and database structures. A
catalog of all data elements, containing their names, structures, and
information about their usage. A central location for metadata. Normally, data
dictionaries are designed to store a limited set of available metadata,
concentrating on the information relating to the data elements, databases, files
and programs of implemented systems.
Data-Driven DSS - This type of DSS emphasizes access to and
manipulation of a time-series of internal company data and sometimes external
data. Simple file systems accessed by query and retrieval tools provide the most
elementary level of functionality. Data warehouse systems that allow the
manipulation of data by computerized tools tailored to a specific task and
setting or by more general tools and operators provide additional functionality.
Data-Driven DSS with On-line Analytical Processing (OLAP) or data mining tools
provide the highest level of functionality and decision support that is linked
to analysis of large collections of historical data. Early, very limited
versions of data-driven DSS were called Retrieval-Only DSS by Bonczek, Holsapple
and Whinston (1981).
Data Element - The most elementary unit of data that can be identified
and described in a dictionary or repository which cannot be subdivided.
Data Mining - A class of analytical applications that search for
patterns in a data base. Data mining is the process of sifting through large
amounts of data to produce data content relationships. Data mining tools use a
variety of techniques including case-based reasoning, data visualization, fuzzy
query and analysis, and neural networks. Case-based reasoning tools provide a
means to find records similar to a specified record or records. These tools let
the user specify the "similarity" of retrieved records. Data visualization tools
let the user easily and quickly view graphical displays of information from
different perspectives.
Data Quality - High quality data is accurate, timely, meaningful, and
complete. DSS must have high quality data; low quality data can result in bad
decisions. Assessing or measuring data quality is a preliminary task associated
with evaluating the feasibility of a data-driven DSS project.
Data Warehouse - A database designed to support decision making in
organizations. It is batch updated and structured for rapid online queries and
managerial summaries. Data warehouses contain large amounts of data. A data
warehouse is a subject-oriented, integrated, time-variant, nonvolatile
collection of data in support of management's decision making process. Check
"What is a Data Warehouse" by W.H. Inmon at
http://
www.cait.wustl.edu/cait/papers/prism/vol1_no1/. According to Ralph Kimball
"A data warehouse is a copy of transaction data specifically structured for
query and analysis" (see Kimball, R. The Data Warehouse Toolkit: Practical
Techniques for Building Dimensional Data Warehouses. 1996. Also, see Greenfield,
L. A Definition of Data Warehousing.)
Data Visualization - This term refers to presenting data and summary
information using graphics, animation, 3-D displays, and other multimedia DSS
tools.
Decision - The choice of one from among a number of alternatives; a
statement indicating a commitment to a specific course of action.
Decision Analysis tools - DA tools help decision makers decompose and
structure problems. The aim of these tools is to help a user apply models like
decision trees, multi-attribute utility models, bayesian models, Analytical
Hierarchy Process (AHP), etc. Examples of DA software packages include
AliahThink, BestChoice3, Criterium Decision Plus, DecideRight, DecisionMaker,
Demos, DPL, Expert Choice, Strad, Supertree, and Which and Why.
Decision Room - A physical arrangement for a group DSS in which
workstations are available to participants. The objective for using a Decision
Roomis to enhance and improve the group's decision-making process.
Decision Systems are computer based programs and technologies intended
to make routine decisions, monitor and control processes, and aid or assist
decision makers in semi-structured and/or non-routine decision situations.
Decision Support Systems (DSS) (Systèmes d'Aide à la Décision) are
interactive computer-based systems intended to help decision makers utilize data
and models to identify and solve problems and make decisions. The "system must
aid a decision maker in solving unprogrammed, unstructured (or "semistructured")
problems...the system must possess an interactive query facility, with a query
language that ...is ...easy to learn and use (Bonczek, Holsapple & Whinston,
1981; p. 19)". DSS help managers/decision makers use and manipulate data; apply
checklists and heuristics; and build and use mathematical models. According to
Turban (1990), a DSS has four major characteristics: DSS incorporate both data
and models; they are designed to assist managers in their decision processes in
semistructured (or unstructured) tasks; they support, rather than replace,
managerial judgment; and their objective is to improve the effectiveness of the
decisions, not the efficiency with which decisions are being made (cf., p. 9).
Decision Variables - In a model-driven DSS a decision variable is a
changing factor in the model that is determined by a decision maker. They are
sometimes called independent variables and the range of values for the decision
variables constrain the choices of the decision maker.
Demon or Daemon - A computer program or procedure that is
automatically activated when it recognizes a specific, predefined state or
condition.
Descriptive Model -Physical, conceptual or mathematical models that
describe situations as they are or as they actually appear.
Deterministic Model - Mathematical models that are constructed for a
condition of assumed certainty. The models assume there is only one possible
result (which is known) for each alternative course or action.
Development Environment - The DE is used by a designer/builder. A
development environment typically includes software for creating and maintaining
a knowledge base and software for the inference engine.
Dialog Generation and Management System (DGMS) - A software management
package in a DSS whose functions in the dialog subsystem is similar to that of a
DBMS in a database (see Sprague and Carlson, 1982, ch. 7).
Dialog System - The hardware and software that create and implement a
user interface for a DSS. A DSS dialog system creates the human-computer
interface.
Document-Driven DSS - It integrates a variety of storage and
processing technologies to provide complete document retrieval and analysis. The
Web provides access to large document databases including databases of hypertext
documents, images, sounds and video. Examples of documents that would be
accessed by a Document-Based DSS are policies and procedures, product
specifications, catalogs, and corporate historical documents, including minutes
of meetings, corporate records, and important correspondence. A search engine is
a powerful decision-aiding tool associated with a Document-Driven DSS (cf.,
Fedorowicz, 1993, pp. 125-136).
Domain Expert - A person who has expertise in the domain in which a
specific expert system is being developed. A domain expert works closely with a
developer (known as a knowledge engineer) to capture the expert's knowledge
(especially rule and relationship information) in a computer readable
representation often called a knowledge base.
Drill Down/Up - An analytical technique that lets a DSS user navigate
among levels of data ranging from the most summarized (up) to the most detailed
(down).
DSS Generator - Computer software package that provides tools and
capabilities that help a developer quickly and easily build a specific Decision
Support System (cf., Sprague and Carlson, 1982, p. 11). Excel is an example of a
DSS Generator. Many companies market tools for building DSS and EIS, see
DSS Vendorlist.
DSS Development Tools - Software components (such as editors, code
libraries, specific objects, visual interfaces) that facilitate the development
of a specific DSS.
e-Meetings - A term for a meeting supported by full-motion video,
audio, and Web meeting tools. One or more participants in the meeting is
participating remotely in the meeting. It is possible that all participants are
in different physical locations.
Enterprise-wide DSS - A DSS that supports a large group of managers in
a networked client-server environment with a specialized data warehouse as part
of the DSS architecture.
Evolutionary (Iterative) Design Process - A systematic process for
system development that is recommended for use in creating DSS. A portion of the
DSS system is quickly constructed, then tested, improved, and enlarged in
systematic steps. This methodology is similar to
prototyping.
Exception Reporting - A reporting philosophy and approach that
supports Management by Exception. Reports should be designed to display
significant exceptions in results and data. The idea is to "flag" important
information and bring it quickly to the attention of managerial users of the
report. Exception reporting can be implemented in any type of DSS, but it is
particularly useful in data-driven DSS and EIS.
Executive Information Systems (EIS) - A computerized system intended
to provide current and appropriate information to support executive decision
making for managers using a networked workstation. The emphasis is on graphical
displays and an easy to use interface that present information from the
corporate database. They are tools to provide canned reports or briefing books
to top-level executives. They offer strong reporting and drill-down
capabilities.
Executive Support Systems (ESS) - An executive information system (EIS)
that includes specific decision aiding and/or analysis capabilities.
Expert Systems are man-machine systems with specialized
problem-solving expertise. The "expertise" consists of knowledge about a
particular domain, understanding of problems within that domain, and "skill" at
solving some of these problems.
Facilitator - A person(s) who manages the use of a group decision
support system from initial planning through actual operation.
Feasibility Study - A study of the technical and economic prospects
for developing a system prior to actually committing resources to actually
developing it.
Functional DSS - A decision support system that holds and derives
knowledge relevant for decisions about some function an organization performs
(e.g., a marketing function, a production function).
Generators - Software packages that are designed to expedite
programming efforts that are required to build information systems, especially
expert and decision support systems.
Goal-seeking - The capability of asking the computer software what
values certain variables must have in order to attain desired goals. It is a
tool that uses iterative calculations to find the value required in one cell
(variable) in order to achieve a desired value in another cell. A common use of
the goal-seeking feature in a spreadsheet is calculating a break-even quantity.
Geographic Information Systems (GIS) - A support system that
represents data using maps. It helps people access, display and analyze data
that have geographic content and meaning. Check U.S. Geological Survey page on
Geographic Information
Systems. Examples of software packages include ArcView, Map/IDIS, Proximity,
and TargetView.
Graphical User Interface (GUI) - A program interface that uses a
computer's graphics capabilities to make the program easier to use. Graphical
interfaces use a pointing device to select objects, including icons, menus, text
boxes, etc. A GUI includes standard formats for representing text and graphics.
Group Decision Support Systems (GDSS) - An interactive, computer-based
system that facilitates solution of unstructured problems by a set of
decision-makers working together as a group. It aids groups, especially groups
of managers, in analyzing problem situations and in performing group decision
making tasks.
Groupware - Is software designed to support more than one person
working on a shared task. Groupware is an evolving concept that is more than
multiuser software which allows access to the same data. Groupware provides a
mechanism that helps users coordinate and keep track of on-going projects. It
allows people to work together through computer-supported communication,
collaboration, and coordination. Lotus Notes, Microsoft Exchange, Communicator,
Novell GroupWise, Netscape SuiteSpot, Eclipse, Team Talk, and Internet
Explorer/NetMeeting are examples of groupware products.
Heuristics - The informal, judgmental knowledge of an application area
that constitutes the "rules of good judgment" in the field. Heuristics also
encompass the knowledge of how to solve problems efficiently and effectively,
how to plan steps in solving a complex problem, how to improve performance, and
so forth. From the Greek-- Heuriskein to discover.
Hypermedia - Combination of several types of media such as text,
graphics, audio, and video.
Hypertext - An approach for handling text and other information by
allowing the users to jump from a given topic, whenever he or she wishes, to
related topics. A knowledge management technique in which knowledge is
represented in linked documents and processed in a way that allows a user to
select a highlighted marker on the currently viewed page to access a linked page
about a topic indicated by the marker.
Icon - A visual, graphic representation of an object, word, or
concept.
Independent Variables - Variables in a model that are controlled by
the environment and that influence the results of a decision (also called Input
Variables, parameters, givens).
Inference - The process of drawing a conclusion from given evidence.
To reach a decision by reasoning.
Inference Engine - That part of an expert system that actually
performs the reasoning function.
Information - Data that has been processed to add or create meaning
and hopefully knowledge for the person who receives it. Information is the
output of information systems.
Information Economics - This term refers to an approach to evaluating
DSS/IS projects using a scoring approach to cost/benefit analysis that assesses
technical and company tangible and intangible benefits and costs (see Parker,
Trainor and Benson, Information Strategy and Economics, 1989.
Information Systems Architecture - A formal definition of the business
processes and rules, systems structure, technical framework, and product
technologies for business information systems. An information systems
architecture consists of four layers: business process architecture, systems
architecture, technical architecture, and product delivery architecture.
Interdependent Decisions - A series of decisions that are
interrelated. A sequential set of decisions are usually interdependent.
Internet - The Internet (capitalized) refers specifically to the DARPA
Internet and the TCP/IP protocols it uses. The Internet is a collection of
packet-switching networks and routers that uses the TCP/IP protocol suit and
functions as a single, cooperative virtual network. A global web connecting more
than one million computers. Visit URL
http://www.wdvl.com/Internet/ for more information about the Internet.
Intranet - An internal organizational network using TCP/IP with at
least one web server that is only accessible by an organization's members or
others who have specific authorization. A firewall and password protection limit
access to the network. The intranet is used to share corporate information,
including DSS capabilities. See
Web-Based DSS examples at
http://dssresources.com/dss/online.html and check the
Intranet FAQ at http://www.intrack.com/
intranet/ifaq.shtml.
Knowledge - Knowledge refers to what one knows and understands.
Knowledge is sometimes categorized as either unstructured, structured, explicit
or tacit. What we know we know is explicit knowledge. Knowledge that is
unstructured and understood, but not clearly expressed is implicit knowledge. If
the knowledge is organized and easy to share then it is called structured
knowledge. To convert implicit knowledge into explicit knowledge, it must be
extracted and formatted.
Knowledge Acquisition - The extraction and formulation of knowledge
derived from various sources, especially from experts.
Knowledge Base - A collection of facts, rules, and procedures
organized into schemas. The assembly of all the information and knowledge of a
specific field of interest.
Knowledge-Driven DSS - Knowledge-Driven DSS can suggest or recommend
actions to managers. These DSS are person-computer systems with specialized
problem-solving expertise. The "expertise" consists of knowledge about a
particular domain, understanding of problems within that domain, and "skill" at
solving some of these problems. A related concept is Data Mining. It refers to a
class of analytical applications that search for hidden patterns in a database.
Data mining is the process of sifting through large amounts of data to produce
data content relationships. Tools used for building Knowledge-Driven DSS are
sometimes called Intelligent Decision Support methods (cf., Dhar and Stein,
1997). Data Mining tools can be used to create hybrid DSS that have major data
and knowledge components.
Knowledge Engineer - An AI specialist responsible for the technical
side of developing an expert system. The knowledge engineer works closely with
the domain expert to capture the expert's knowledge in a knowledge base.
Knowledge Engineering (KE) - The engineering discipline that involves
integrating knowledge into computer systems in order to solve complex problems
normally requiring a high level of human expertise.
Knowledge Management (KM) - KM is the distribution, access and
retrieval of unstructured information about "human experiences" between
interdependent individuals or among members of a workgroup. Knowledge management
involves identifying a group of people who have a need to share knowledge,
developing technological support that enables knowledge sharing, and creating a
process for transferring and disseminating knowledge.
Knowledge Management Software (KMS) - Software that can store and
manage unstructured information in a variety of electronic formats. The software
may assist in knowledge capture, categorization, deployment, inquiry, discovery,
or communication. Products include electronic document management systems (EDMS).
Visit KMWorld.
Linear Programming - A mathematical model for optimal solution of
resource allocation problems.
Metadata or Meta Data - Data about the data in a data warehouse.
Metadata provides a a directory to help the DSS locate the contents of the data
warehouse; it is a guide to mapping data as it is transformed from the
operational environment to the data warehouse environment; and it serves as a
guide to the algorithms used for summarization of current detailed data.
Metadata is semantic information associated with a given variable. Metadata must
include business definitions of the data and clear, accurate descriptions of
data types, potential values, original source system, data formats, and other
characteristics. Metadata defines and describes business data. Examples of
metadata include data element descriptions, data type descriptions,
attribute/property descriptions, range/domain descriptions, and process/method
descriptions. The repository environment encompasses all corporate metadata
resources: database catalogs, data dictionaries, and navigation services.
Metadata includes things like the name, length, valid values, and description of
a data element. Metadata is stored in a data dictionary and repository. It
insulates the data warehouse from changes in the schema of operational systems.
Methodology - A system of principles, practices, and procedures
applied to a specific branch of knowledge.
Middleware - A communications layer that allows applications to
interact across hardware and network environments.
Model Base - A collection of preprogrammed quantitative models (e.g.,
statistical, financial, optimization) organized as a single unit.
Model-Driven DSS or Model-oriented DSS - This type of DSS emphasizes
access to and manipulation of a model, e.g., statistical, financial,
optimization and/or simulation. Simple statistical and analytical tools provide
the most elementary level of functionality. Some OLAP systems that allow complex
analysis of data may be classified as hybrid DSS systems providing both modeling
and data retrieval and data summarization functionality. Data mining is also a
hybrid approach to DSS. In general, model-driven DSS use complex financial,
simulation, optimization and/or rule (expert) models to provide decision
support. Model-driven DSS use data and parameters provided by decision makers to
aid decision makers in analyzing a situation, but they are not usually data
intensive, that is very large data bases are usually not need for model-driven
DSS. Early versions of model-driven DSS were called Computationally Oriented DSS
by Bonczek, Holsapple and Whinston (1981).
Modeling Tools - Software programs that help developers/users build
mathematical models quickly. Spreadsheets and planning languages like IFPS are
modeling tools.
Multi-dimensional Database (MDBS and MDBMS) - A database that lets
users analyze large amounts of data. An MDBS captures and presents data as
arrays that can be arranged in multiple dimensions. Variables are the objects
that hold data in a multidimensional database. These are simply arrays of values
(usually numeric) that are "dimensioned" by the dimensions in a database. For
example, a UNITS variable may be dimensioned by MONTH, PRODUCT, and REGION. This
three-dimensional variable or array is often visualized as a cube of data.
Multi-dimensional databases can have multiple variables, with common or a unique
set of dimensions. This multi-dimensional view of data is especially powerful
for OLAP applications.
Multiparticipant DSS - A decision support system that supports
multiple participants engaged in a decision-making task (or functions as one of
the participants). See group DSS.
Multipoint Conference - An audio, data and/or video conference among
more than tworemote participants.
Multipoint Control Unit (MCU) - A device used to link remote sites
into a single conference call or a device to manage several simultaneous,
independent conferences.
Normalization - The process of reducing a complex data structure into
its simplest, most stable structure. In general, the process entails the removal
of redundant attributes, keys, and relationships from a conceptual data model.
Object - A person, place, thing, or concept that has characteristics
of interest to an environment. In terms of an object-oriented system, an object
is an entity that combines descriptions of data and behavior.
On-line Analytical Processing (OLAP) - Software for manipulating
multidimensional data from a variety of sources that has been stored in a data
warehouse. The software can create various views and representations of the
data. OLAP software provides fast, consistent, interactive access to shared,
multidimensional data. Check the
Guide to OLAP
Terminology from the OLAP Council
Operational or Transaction Database - The database-of-record for a
transaction-update system. The operational database is the source of data for
the data warehouse. It contains detailed data used to run the day-to-day
operations of the business. The data continually changes as updates are made,
and reflect the current value of the last transaction.
Optimize - The decision strategy of choosing the alternative that
gives the best or optimal overall value.
Organizational DSS - A multiparticipant DSS designed to support a
decision maker in a setting that has a more elaborate infrastructure than a
group (i.e., involving specialized roles, restricted communication patterns,
differing authority levels). See enterprise-wide DSS.
Pivot - Changing the dimensional orientation of a display or report.
See rotate in the
OLAP Guide to terms.
Planning - A managerial function concerned with making forecasts,
formulating outlines of things to do, and identifying methods to accomplish
them.
Prototyping - A strategy in system development in which a scaled down
system or portion of a system is constructed in a short time, tested, and
improved in several iterations. A prototype is an initial version of a system
that is quickly developed to test the effectiveness of the overall design being
used to solve a particular problem. Prototyping is similar to the Evolutionary
(Iterative) Design Process. It is sometimes termed rapid prototyping and is
similar to rapid application development (RAD).
Query - Generically query means question. Usually it refers to a
complex SQL SELECT statement for decision support. See Ad-Hoc Query or Ad-Hoc
Query Software.
Rapid Application Development (RAD) - Part of a methodology that
specifies incremental development with constant feedback from the customers. The
point is to keep projects focused on delivering value and to keep clear and open
lines of communication. Oral and written communication is not completely
adequate for specification of computer systems. RAD overcomes the limitations of
language by minimizing the time between concept and implementation.
Rational Decision Behavior -Behavior that is goal-oriented in reaching
a decision. Behavior is guided by the consequences likely to result from the
selection of a given alternative. A decision maker believes based upon analysis
that a chosen alternative will result in achieving one or more desired
objectives. Rational decision behavior should be supported by DSS.
Record - A group of data values consisting of one value for each of a
prescribed set of relational fields; an occurrence of a record type.
Report and Query tools - these tools produce a of tabular list of
information from data stored in a relational database. Examples include
Microsoft Access and Brio Query.
Representation - The formulation or view of a problem. Developed so
the problem will be easier to solve.
Result Variables - In a model-driven DSS a result variable shows the
consequences of changing decision variables. Result variable are also referred
to as dependent variables.
ROMC (Representation, Operations, Memory Aids, Mechanism Control) Design
Approach - A Systematic approach for developing large-scale DSS, especially
user interfaces. It is user-oriented approach for stating system performance
requirements (cf., Sprague and Carlson, 1982).
Rule - A formal way of specifying a recommendation, directive, or
strategy, expressed as IF premise THEN conclusion.
Scalability - The ability to scale hardware and software to support
larger or smaller volumes of data and more or less users. The ability to
increase or decrease size or capability in cost-effective increments with
minimal impact on the unit cost of business and the procurement of additional
services.
Semistructured Decisions - Decisions in which some aspect of the
problem are structured and others are unstructured.
Sensitivity Analysis - running a decision model several times with
different inputs so a modeler can analyze the alternative results.
Shell - An expert system development tool consisting of two
stand-alone pieces of software: a rule set manager and an inference engine
capable of reasoning with rules set built with the rule set manager. A shell is
a complete expert system stripped of its specific knowledge.
Simulation - A technique for conducting one or more experiments that
test various outcomes resulting from a quantitative model of a system.
Specific DSS - A computer-based system that actually helps a person
accomplish a specific task. "Specific DSS are the hardware/software that allow a
specific decision maker or group of them to deal with specific sets of related
problems" (cf., Sprague and Carlson, 1982, p. 10).
Spreadsheet - In the accounting world a spreadsheet was and is a large
sheet of paper that lays everything out for a businessperson. It spreads or
shows all of the costs, income, taxes, etc. on a single sheet of paper for a
manager to look at when making a decision. An electronic spreadsheet organizes
information into columns and rows. The data can then be "added up" by a formula
to give a total or sum. The spreadsheet summarizes information from many sources
in one place and presents the information in a format to help a decision maker
see the financial "big picture" for the company. A program that has a collection
of cells whose values can be displayed on a computer screen. By changing cell
definitions and having all cell values reevaluated, a user can readily observe
the effects of those changes. Decision support systems built using spreadsheet
software are sometimes called Spreadsheet DSS. See
"A Brief History of
Spreadsheets" by Daniel Power.
Star Schema - A relational database schema organized around a central
table (fact table) joined to a few smaller tables (dimension tables) using
foreign key references. The fact table contains raw numeric items that represent
relevant business facts (price, discount values, number of units sold, dollar
value, etc.) The facts are typically additive and are accessed via dimensions.
Since the fact tables are presummarized and aggregated along business
dimensions, these tables tend to be very large. The basic premise of star
schemas is that information can be classified into two groups: facts and
dimensions. Facts are the core data element being analyzed. For example, units
of individual items sold are facts, while dimensions are attributes about the
facts. Dimensions are the product types purchased and the date of purchase. The
star schema has also been called a star-join schema, data cube, data list, grid
file, and multidimensional schema. The name star schema comes from the pattern
formed by the entities and relationships when they are represented as an
entity-relationship diagram (ERD). The results of a business activity are at the
center of the star surrounded by the people, places, and things that come
together to perform this activity. These dimensions are the points of the star.
Strategic Planning - A decision-making process in which decisions are
made about establishing organizational purposes/mission, determining objectives,
selecting strategies and setting policies.
Structured Decisions - Standard or repetitive decisions situations for
which solution techniques are already available (also sometimed called routine
or programmed decisions). The structural elements in the situation, e.g.
alternatives, criteria, environmental conditions, are known, defined and
understood.
Symbolic Processing - Use of symbols, rather than numbers, combined
with rules-of-thumb (or heuristics), in order to process information and solve
problems.
Systems Development Life Cycle (SDLC) - A process by which systems
analysts, software engineers, programmers, and end-users build systems. It is a
project management tool, used to plan, execute,, and control systems develpment
projects. The steps in the cycle include: 1) Determine user requirements; 2)
Systems analysis; 3) Overall system design; 4) Detailed system design; 5)
Programming; 6) Testing; and 7) Implementation. Each step is concluded by
developing a written document that must be reviewed and approved before the next
step begins.
Ticker - A small Java Applet that displays a specific set of
headlines, information, etc.. Every web page that wants to display a Ticker must
add some special HTML code into the page. This code ensures that the JAVA Applet
is loaded from a server. Some parameters control the visible output like
coloring and of course they control which news are loaded. Visit
http://7am.com/ticker/ or
http://www.tickerland.com/
Unstructured Decisions - This type of decision situation is complex
and no standard solutions exist for resolving the situation. Some or all of the
structural elements of the decision situation are undefined, ill-defined or
unknown. For example, goals may be poorly defined, alternatives may be
incomplete or non-comparable, choice criteria may be hard to measure or
difficult to link to goals.
User-Friendly - An evaluative term for a Decision Support System's
user interface. The phrase indicates that users judge the user interface as to
easy to learn, understand, and use.
User Interface (or "Human-Computer Interface") - The component of a
computerized support system that allows bidirectional communication between the
system and its user. This is also called the dialogue component of a DSS. An
interface is a set of commands or menus through which a user communicates with a
program.
Web-based DSS - A computerized system that delivers decision support
information or decision support tools to a manager or business analyst using a
"thin-client" Web browser like Netscape Navigator or Internet Explorer. The
computer server that is hosting the DSS application is linked to the user's
computer by a network with the TCP/IP protocol. In many companies, a Web-based
DSS is synonymous with an enterprise-wide DSS that is supporting large groups of
managers in a networked client-server environment with a specialized data
warehouse as part of the DSS architecture.
"What If" Analysis - The capability of "asking" the software package
what the effect will be of changing some of the input data or independent
variables.
Power, D. J. Decision Support Systems Glossary. DSS Resources, World
Wide Web, http://DSSResources.COM/glossary/, 1999.
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