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Transcript
DECISION SUPPORT SYSTEM
ARCHITECTURE:
The data management component
Data Collection
SOURCE: Primary / Secondary or
External / Internal / Personal
TYPE: ‘Hard’ / ‘Soft’
LEVEL: Strategic / Tactical / Operational
What are the problems with data collection? What gives
information quality?

ACCURACY

TIMELINESS

RELIABILITY

RELEVANCE

COMPLETENESS

CURRENCY

INTERPRETABILITY

PRESENTATION

ACCESSIBILITY
The Data Management sub system
of a DSS




Extracts information from internal company
databases (specialised integrated database or
data warehouse)
Has links to external data sources (Web access)
Interfaces with modelling capabilities, user
interface design.
May have a knowledge component (AI
capabilities)
Database Management Systems


A DBMS enables greater
integration of data, complex file
structure, user query facilities.
e.g. The university’s DBMS is
Oracle. The query facility is
through the language SQL
The main type of DSS database
organisation is relational.
Data Warehouses


The combination of many data sources into one
store, specifically for end user access. This store is
separate from the organisation’s records of
operations (transaction processing system files)
but partly derived from them.
Appropriate in large organisations with different
systems which may store the same data for
different needs and in different formats.

Data warehousing provides a means for integrating
the data from the various systems.

Useful for static (usually historical) data
Data Mining
a.k.a. data exploration or data pattern processing


The need for tools to help with data access is due to
the complexity and size of many organisation’s
databases (data warehouses)
The query can be conducted quickly, and the miner
does not need programming skills to explore the
database (end user support)

A focus on discovery vs verification

On line Analytical Processing – multidimensional
databases

Problems with data warehouses/ data mining may
be Data Noise, Missing information, Security,
Reliability
Data Visualisation
Incorporates any technology that allows the
user to picture the information in a more
meaningful way.




GUI (windows and icons applications
graphical facilities
GIS (geographical information systems)
3D presentations/ animation
Continuing Research and
Development
Progress over time…………………….
DATA
sources
INFORMATION
sources
KNOWLEDGE
sources
tables/ lists
documents
expertise, experience
facts/ figures
concepts, opinions, best practice cases
verbal reports
shared practice
“hard data”
“soft data”
intelligence
Continuing Research…..

Intelligent component



Intelligent agents (‘detect and alert’
capabilities) on the Internet
Case based reasoning and neural
networks (pattern recognition
capabilities)
Web integrated database systems