1. DBMiner 2.0 Adnan Rahi Prabhat Vivekanandan

2. 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

3. General architecture of DBMiner

4. 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.

5. 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

6. DBMiner user interfaces UNIX-based Windows/NT-based WWW/Netscape-based

7. DBMiner Wizard

8. OLAP Browser

10. 3-D Cube

11. Association

12. Association Settings

13. Classification

14. Classification Settings

15. Clustering

16. Clustering Settings

17. 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

18. Methodology 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.

19. 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

20. Capability 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

21. 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!

22. 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

23. 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

24. Interoperability 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.

25. Flexibility 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.

26. 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.

27. Capability, Learnability/Usability, Interoperability, and Flexibility ExcellentGoodAverageNeeds ImprovementPoorDoes Not Exist Scalability  Has programming language  Provides useful output reports  Visualization  Wizards  Easy to learn  User’s manual  Online help  Interface  Importing data  Exporting data  Links to other applications  Customizable work environment  Ability to write or change codes  Overall 

28. Any Questions?