introduction to data mining rafal lukawiecki strategic consultant, project botticelli ltd...

Download Introduction to Data Mining Rafal Lukawiecki Strategic Consultant, Project Botticelli Ltd rafal@projectbotticelli.co.uk

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Introduction to Data Mining Rafal Lukawiecki Strategic Consultant, Project Botticelli Ltd rafal@projectbotticelli.co.uk Slide 2 2 Objectives Overview Data Mining Introduce typical applications and scenarios Explain some DM concepts Review wider product platform The information herein is for informational purposes only and represents the opinions and views of Project Botticelli and/or Rafal Lukawiecki. The material presented is not certain and may vary based on several factors. Microsoft makes no warranties, express, implied or statutory, as to the information in this presentation. 2007 Project Botticelli Ltd & Microsoft Corp. Some slides contain quotations from copyrighted materials by other authors, as individually attributed. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Project Botticelli Ltd as of the date of this presentation. Because Project Botticelli & Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft and Project Botticelli cannot guarantee the accuracy of any information provided after the date of this presentation. Project Botticelli makes no warranties, express, implied or statutory, as to the information in this presentation. E&OE. This seminar is partly based on Data Mining book by ZhaoHui Tang and Jamie MacLennan, and also on Jamies presentations. Thank you to Jamie and to Donald Farmer for helping me in preparing this session. Thank you to Roni Karassik for a slide. Thank you to Mike Tsalidis, Olga Londer, and Marin Bezic for all the support. Thank you to Maciej Pilecki for assistance with demos. Slide 3 3 Before We Dive In... To help me select the most suitable examples and demonstrations I would like to ask you about your background Who do you identify yourself with: IT Professional, Database Professional, Software/System Developer? Slide 4 4 The Essence of Data Mining as Part of Business Intelligence Slide 5 5 Business Intelligence Improving Business Insight A broad category of applications and technologies for gathering, storing, analyzing, sharing and providing access to data to help enterprise users make better business decisions. Gartner Slide 6 6 Relationships And Acronyms... Data Mining (DM) Knowledge Discovery in Databases (KDD) Business Intelligence (BI) Slide 7 7 Data Mining Technologies for analysis of data and discovery of (very) hidden patterns Fairly young (

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