1. Peter Myers Bitwise Solutions Pty Ltd

6. Predictive Analytics PresentationExplorationDiscovery Passive Interactive Proactive Business Insight Canned Reporting Ad hoc Reporting Data Model Data Mining Role of Software

7. Data Mining Seek Profitable Customers Understand Customer Needs Anticipate Customer Churn Predict Sales and Inventory Build Effective Marketing Campaigns Detect and Prevent Fraud Correct Data During ETL

8. “Putting Data Mining to Work” “Doing Data Mining” Business Understanding Data Understanding Data Preparation Modeling Evaluation Deployment Data www.crisp-dm.org

10. Design time Process time Query time Mining Model

11. Design time Process time Query time Mining Model Training Data Data Mining Engine

12. Design time Process time Query time Data Mining Engine Data to Predict Predicted Data Mining Model

18. Classify Decision Trees Logistic Regression Naïve Bayes Neural Networks Estimate Decision Trees Linear Regression Logistic Regression Neural Networks Cluster Clustering Forecast Time Series Associate Associatio n Rules Decision Trees

20. Data Mining Interfaces Analysis Server OLAPData Mining Server ADOMD.NET.NET Stored Procedures Microsoft Algorithms Third-Party Algorithms WAN XMLA Over TCP/IP OLE DBADOADO.NET XMLA Over HTTP Any Platform, Any Device C++ AppVB App.NET AppAny App AMO

24. http://msdn.microsoft.com/en-au/ http://www.microsoftvirtualacademy.com/ http://channel9.msdn.com/Events/TechEd/Australia/2013 http://technet.microsoft.com/en-au/