dbminer 2 0 n.
Skip this Video
Loading SlideShow in 5 Seconds..
DBMiner 2.0 PowerPoint Presentation
Download Presentation
DBMiner 2.0

Loading in 2 Seconds...

play fullscreen
1 / 28

DBMiner 2.0 - PowerPoint PPT Presentation

  • Uploaded on

DBMiner 2.0. Adnan Rahi Prabhat Vivekanandan. Brief History of DBMiner Technology Inc. Research on data mining since 1989. International reputation and recognition. Substantial research supports and contracts. DBMiner Technology Inc.: A Simon Fraser University Spin-Off Company

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'DBMiner 2.0' - mairead

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
dbminer 2 0
DBMiner 2.0
  • Adnan Rahi
  • Prabhat Vivekanandan
brief history of dbminer technology inc
Brief History of DBMiner Technology Inc.
  • Research on data mining since 1989.
  • International reputation and recognition.
  • Substantial research supports and contracts.
  • DBMiner Technology Inc.: A Simon Fraser University Spin-Off Company
  • Incorporated in March 1997, dedicated to data mining system development and commercialization.
  • Major products: DBMiner 2.0 (Enterprise)
    • Customization and application-oriented data mining systems
    • GeoMiner, WebMiner, WebLogMiner, …, more miners in progress
distinct features of dbminer
Distinct Features of DBMiner
  • Multiple data mining functions.
    • OLAP service, cube exploration, statistical analysis, classification (market/customer segmentation, decision trees), association (basket data analysis), cluster analysis, etc.
  • On-line analytical mining of Microsoft/ PLATO OLAP cube.
  • Data and knowledge visualization tools: visual data mining.
  • OLEDB and RDBMS connections.
dbminer features
DBMiner Features
  • It incorporates several interesting data mining techniques
    • attribute-oriented induction
    • progressive deepening for mining multiple-level rules
    • meta-rule guided knowledge mining
  • Implements a wide spectrum of data mining functions
    • generalization
    • characterization
    • association
    • Classification
    • Clustering
dbminer user interfaces
DBMiner user interfaces
  • UNIX-based
  • Windows/NT-based
  • WWW/Netscape-based
how did we evaluate
How did We Evaluate?
  • we have used FoodMart database
    • comes with MS SQL server
    • made up of two cubes: Sales and Warehouse
  • hardware features
    • Pentium 166 MHZ with 64 MB RAM, running Windows 2000
  • capability:measures what a desktop tool can do, and how well it does it
    • scalability
    • has programming language
    • provides useful output reports
    • has visualization capabilities
  • learnability/Usability:how easy a tool is to learn and use
    • tutorials
    • wizards
    • easy to learn
    • user’s manual
    • online help
    • interface.
methodology cont
Methodology (Cont.)
  • interoperability: tool’s ability to interface with other computer applications
    • importing data
    • exporting data
    • links to other applications
  • flexibility: the ease with which one can alter critical guiding parameters, or create a customized environment
    • customizable work environment
    • ability to write or change codes
  • the scalability factor of the software was efficient
  • uses DMQL (Data Mining Query Language)
    • the user is not able to manipulate the DMQL.
  • the visualization part of the software uses many graphics including ball graph, ball chart, grid, and frequent item sets
    • pie charts and correlation plots were missing
    • tree browsing was in graph view, which was confusing
    • OLAP browser, uses MS Excel 2000 visualization capabilities
capability cont
Capability (Cont.)
  • DBMiner shows the statistics report
    • does not analyze the statistical results
    • the statistics report is too short
  • we were not able to print any of results from Associations, Classifications, and Clustering, as well as the statistics results
    • the page was blank!
learnability usability
  • DBMiner is not a complex program for people familiar with data mining
  • does not include a tutorial to walk you through with an example
  • wizards are built in for automating the tasks of data mining
    • let the user select appropriate options for the tasks
  • the user interface is very simple and standard
  • tool bars did not perform very well when enabled
    • for example, tools in the visualization pane
learnability usability cont
Learnability/Usability (Cont.)
  • some of the commands under menus do not have any function associated with them
    • “Export” command under the file menu
  • the user’s manual is well constructed for a user to find appropriate way to explore
    • the style of the user’s manual is old, not web fashioned
    • does not contain links to other relevant topics
  • has a good on line help
    • pressing F1 shows help topic
    • most dialog boxes have help button
  • does not support importing and exporting of data
  • communicates with MS OLAP Server and has MS Excel 2000 embedded as a visualization tool for OLAP browsing.
  • it is not possible to change or write DBQL
  • has the flexibility to let the user change the values of settings after each task is done
      • it is possible to increase/decrease the support threshold or the confidence threshold if the user is not happy with the current level.
other limitations
Other Limitations
  • depends only on MS SQL Server as its back-end
  • uses MS Excel 2000 as its visualization tool for OLAP browsing
  • unavailable functional modules
    • data dispersion module
    • time-serial analysis module
    • prediction module.
capability learnability usability interoperability and flexibility




Needs Improvement


Does Not Exist


Has programming language

Provides useful output reports



Easy to learn

User’s manual

Online help


Importing data

Exporting data

Links to other applications

Customizable work environment

Ability to write or change codes


Capability, Learnability/Usability, Interoperability, and Flexibility