Download Lecture Outline Learning Objectives

DocumentDocument-Driven,
CommunicationsCommunications-Driven and
Group Business Intelligence
Systems
Week 12
Dr. Jocelyn San Pedro
School of Information Management &
Systems
Monash University
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
Lecture Outline
ƒ Document-Driven BIS
ƒ Communications-Driven BIS
ƒ Group BIS
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
2
Learning Objectives
At the end of this lecture, the students will
ƒ
ƒ
Gain some understanding of concepts and technologies in
document-driven, communications-driven and group BIS
Gain some understanding of 4 essential elements in
developing and building BIS
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
3
1
Document-Driven BIS
information systems that provide BI through access and
manipulation of unstructured, semi-structured or wellstructured documents
Document Management Systems
Content Management Systems
Knowledge Management Systems
BI Tools
Drill down
Drill up
Text mining
Web Mining
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
4
Document Management Systems
information systems that integrate a variety of storage
and processing technologies to provide complete
document retrieval and analysis (Power 2002)
ƒ capture, find, access, search for content, review, organise,
edit [with trail logging and versioning], approve, share
ƒ integrate workflow (document’s lifecycle)
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
5
Sample Document Management System
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
http://www.lacertesoftware.com/products/p_dms.cfm
6
2
Content Management Systems
information systems that supports the creation,
management, distribution, publishing, and
discovery of corporate information
ƒ provide tools for completing lifecycle of web site pages
ƒ create, publish, archive contents
ƒ manage the structure of the site, the appearance of the
published pages, and the navigation provided to the users.
http://www.steptwo.com.au/papers/kmc_what/index.html
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
7
Sample Content Management System
Architecture
http://www.knowledgebase.net/
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
8
Knowledge Management Systems
ƒ A system for managing the gathering, refining, analysing,
disseminating of knowledge in all forms within an
organisation
ƒ A system that supports organisational functions while
addressing the needs of the individual within a purposeful
context
Charles and Jackson (www.brint.com/km/)
Knowledge Management – a broad concept that addresses the
full range of processes by which an organisation deploys
knowledge. This includes acquisition, distribution and use of
knowledge by the organisation.
Burstein and Linger (IMS3012, www.sims.monash.edu.au)
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
9
3
Sample Knowledge Management
Systems
www.sigmaconnect.com
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
10
BI Tools
Drill-up
ƒ Summarise subject-oriented document data warehouses
ƒ Categorise documents
Drill-down
ƒ Actual object or document (image, hypertext documents,
sound, video)
Sample Doc-Driven BIS: Infozoom –visual data mining (zoom
in to focus on details, zoom out to visually summarise data)
http://www1.ics.uci.edu/~kobsa/courses/ICS280/notes/papers/spenkebeilken.pdf
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
11
HumanIT Infozoom – Sample
DocumentDocument-Driven BIS
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
http://www1.sapdesignguild.org/editions/edition2/info_zoom.asp
12
4
BI Tools
Text mining
ƒ searching large volumes of documents for certain keywords
or key phrases to reveal various relationships between the
documents
ƒ looking for regularities, patterns or trends in natural
language text
ƒ analysing text for particular purposes
ƒ aiming at extracting useful knowledge from unstructured or
semi-structured text
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
13
BI Tools
Text Mining
Data mining approach – text as collection of strings
ƒ statistical techniques
ƒ AI/soft computing technologies
ƒ e.g keyword search, routing, filtering, classifications,
associations, sequencing, clustering
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
14
BI Tools
Natural Language Processing approach (aka
computational linguistics)
ƒ statistics, machine learning, reasoning, information
extraction, knowledge management, cognitive science
ƒ e.g. reference citations – people, companies, places to
answer who, what, where questions
ƒ e.g. summarising texts, deriving context of citation
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
15
5
BI Tools
Sample applications:
ƒ Deriving common patterns from comments in survey
feedbacks
ƒ Summarising/analysing document content
ƒ Developing tree-like topic structure
ƒ Sample BIS – TextAnalyst (www.megaputer.com)
ƒ semantic information retrieval and focused text
exploration around a certain subject
ƒ linguistic and neural network technologies
http://www.dmreview.com/editorial/dmreview/print_action.cfm?articleI
d=5415
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
16
BI Tools
Web mining – combined data mining + text mining
ƒ
ƒ
ƒ
ƒ
ƒ
Enhances intelligent behaviour in Web sites
Learning from user’s favourite sites, interests, preferences
Suggesting related links based on user’s profile
Revealing clickstream patterns
Sample BIS
ƒ Maxamine Web Analyst
www.maxamine.com/webanalyst/
ƒ Megaputer’s Web Analyst www.megaputer.com
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
17
Sample BIS with Text/Web Mining Tools
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
18
6
Sample BIS with Text/Web Mining Tools
Similarity
based on
context,
sentence
level, text
level, etc
http://citeseer.ist.psu.edu/cis
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
19
Sample BIS with Text/Web Mining Tools
Subject
relationship –
based on
reference lists
sharing similar
sources
http://isi10.isiknowledge.com/portal.cgi/wos
IMS3001
– BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
20
CommunicationsCommunications-Driven, Group BIS
information systems that provide BI through communications,
collaboration, negotiations among members of team, group,
or organisation structure
Group Support Systems
Negotiation Support Systems
Computer Supported
Collaborative Work Systems
(CSCWS)
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
BI Tools
Drill down
Drill up
Text Mining
Web Mining
Advanced BI
Tools
21
7
SpatialSpatial-temporal Dimensions of
Communication modes
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
22
CommunicationsCommunications-Driven, Group SS
Sample Systems and Mode of Communication
ƒ
eBay - e-market place; e-negotiation support (STDP)
http://www.pages.ebay.com/immaina6.html
ƒ
Opinions-online (incl. e-voting)
(DTDP)
http://www.opinions.hut.fi/introduction.html
ƒ
MindManager - Brainstorming systems
(STSP)
http://www.mindjet.com/
ƒ
MSN Messenger
(STDP)
http://ninemsn.com.au/
ƒ
Netscape Calendar Express
(DTSP)
http://calendar1.monash.edu.au
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
23
Sample CSCWCSCW- Sparrow Web –
Community shared web pages
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
24
http://sparrow10.parc.xerox.com:8000/sparrow_2.0/sparrowhome.html
8
CommunicationsCommunications-Driven, Group BIS
Networked environments
ƒ Aged and real-time data
ƒ WWW - refers to all of the publicly accessible web sites in
the world, in addition to other information sources that web
browsers can access.
ƒ Internet - refers to the worldwide network of interconnected
computers
ƒ Intranet - any network of interconnected computers
belonging to one organisation, similar to but separate from
or insulated from the Internet.
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
25
Example : Virtual Trading Floor at NYSE
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
http://www.nyse.com/
26
Developing and Implementing BIS
4 Essential Elements
ƒ
ƒ
ƒ
ƒ
Employing current information systems
Utilising data mining and BI methods and software
Building effective data warehouses and real-time
computing systems
Making greatest use of E-commerce related computer
networking
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
27
9
Data Mining and BI Software
Data mining
ƒ Angoss Software Intl, Business Objects, Cognos, DataMind,
Information Discovery, Magnify, NeoVista, Pilot Software,
SAS Institute, Thinking Machines
BI
ƒ Brio, Business Objects, Cognos, Hummingbird, IBM,
Informix, Platinum, SAS Institute, Seagate, Sybase,
PeopleSoft, SAP, Oracle
Open platform – Microsoft SQL Server 7.0 or IBM’s DB2
UDB
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
28
References
Marakas, G.M. (2002) Decision support systems in the 21st
Century. 2nd Ed, Prentice Hall (or other editions)
Power, D. (2002) Decision Support Systems: Concepts and
Resources for Managers, Quorum Books.
Thierauf, R. (2001) Effective Business Intelligence Systems,
Quorum Books.
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
29
Questions?
[email protected]
School of Information Management and Systems, Monash
University
T1.28, T Block, Caulfield Campus
9903 2735
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
30
10