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An Overview of Data Mining with The SAS System Gerhard Held SAS Institute European Product Manager Analysis Applications Data Mining The Flood of Data and Data Mining What is Data Mining? - The DM Process Why Data Mining? - Applications SAS Institute and Data Mining Conclusion S The Flood of Data and Data Mining The Goal: “Knowledge is the only competitive Advantage” Jack Welch, CEO, General Electric S The Flood of Data and Data Mining The current Situation: “Computers promised us a Fountain of Wisdom, but delivered us a Flood of Data” Gregory Piatetsky-Shapiro, 1991 S The Flood of Data and Data Mining Data Warehousing Ideal for Data Mining Operational RDBMS EIS Data Extractor Transformation Engine OLAP Risk Metadata Data Mining Query and Reporting Legacy SAS Information Database Internet Exploitation Metadata Manager Intelligent Client/Server External Organisation Product Data Visualisation OO RAD Management Customer DSS Loader Scheduler Quality Exploitation Market Future S What is Data Mining? Who are my best Customers in Region X? OLAP What Sort of Customers should I target? Data Mining S What is Data Mining? Unspecific Questions “Advanced Methods of exploring and modelling Relationships in large Amounts of Data” S What is Data Mining? Unspecific Questions “Advanced Methods of exploring and modelling Relationships in large Amounts of Data” DM is a Set of Techniques S What is Data Mining? DM is a Technique, not an Application DM consists of many Techniques: Visual Exploration Clustering, Factor, Correspondence Tree-based Models Time Series Analysis Neural Networks Statistical Modelling S Data Mining Unspecific Questions “Advanced Methods of exploring and modelling relationships in large Amounts of Data” DM is a Set of Techniques DM is a Process S Data Mining as a Process Business / IT Environment DBMS Data Warehouse Data Mining Internal Processing Business Reporting and Graphics Informed Business Decisions S Sample Visual Exploration Variable grouping, subsetting Neural Networks Tree-based Models Assess Sampling ? Explore Manipulate Model Data Update ? New Questions ? Sample Clustering, Factor, Correspond. Adding or subsetting of Records Statistical Techniques Assess Time Series Analysis The Data Mining Process Sampling? A clear Pattern will also show in a Sample Enormous Performance Advantages Random Sampling, Stratification, etc. S The Data Mining Process Exploration Visual Exploration: Multidimensional, Graphical Data Analysis, Geographical Visualisation Statistical Visualisation: Cluster, Factor, Correspondence, MDS,… Groups, important Variables S The Data Mining Process Manipulation Variable Selection New Variables: Groups, etc. Significant Subgroups? S The Data Mining Process Modelling Neural Networks Tree-based Models Generalised Linear Models Time Series Analysis Specific Market Research Methods S The Data Mining Process Assessment “Survival of the Fittest” Generate New Questions - Iterative Process S Why Data Mining? - Industries Retail: Direct Mail: Multimedia: Banks: Insurances: Telecomms: POS Data, Customer Transactions Customer Orders, Credit Data Books, Video, Internet Usage Stock Data, Account Data, Credit Data Claims Data, Benefit Payments Data Call Centres, Customer Data S Why Data Mining? - Applications Marketing: Customer Segmentation: The most profitable Customers Database Marketing: Which Prospects, which Products? Customer Attrition: Which Groups are in Danger? Media Analysis: Print Media, TV, Internet... S Why Data Mining? - Applications Sales / Finance: Sales Forecasting - Historical Data and current influential Trends Credit Approval: Credit Risk and Credit Scoring Fraud Detection: Insurances, Banks, Credit Card Companies Portfolio Analysis S Why Data Mining - Applications Others: Forecasting of maximal CPU Usage Demand of Electricity, Water etc. Simulation of chemical or discrete Manufacturing Processes ... S Data Mining - References Our customers have been successful at Data Mining because SAS Institute treats it as an information process. Neckermann, D Ellos, S Credit Scoring Customer Segmentation, Campaign Management Postbank NV, NL same UTAC, F Vehicle Test Results Tracking more: Inform 16 - Database Marketing S SAS Institute and Data Mining DM Methods: NNA - Initial Prod. July (UNIX) Tree Menue System (Sample), thanks to SAS UK! Everything else Production Software: Exploration: INSIGHT, SPECTRAVIEW, GIS Statistics Time Series Forecasting Market Research Methods S SAS Institute and Data Mining More Information on Data Mining: This Data Mining Stream DM White Paper Exhibition Area: Booth 2 Data Mining / Database Marketing Technology Centre Booth 5 Exploiting the Data Warehouse Systems Stream Paper Press Announcement The Meta Group: MetaFax on Data Mining S Conclusion - Data Mining SAS Software Benefits for Data Mining: Access to all Data Sources (DBMS, Data Warehouses, Others) Complete Set of Technologies: NNs, Trees, Visualisation, Statistics (Gartner Group) Unique Methodology: SEMMA S Conclusion - Data Mining ??? S Conclusion - Data Mining S Conclusion - Data Mining Sample Explore Manipulate Model Assess S Thank you for your attention The SAS® System for successful decision making
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