1. Data Mining and ERP Presented by: Abhineet Malviya Ankesh Jindal Mayur Shinde

2. Agenda Data Mining and Knowledge Discovery Basics ERP Vendors and Data Mining Solutions Pro and Cons of ERP centric Data Mining

3. What is Data Mining and Knowledge Discovery ? Data Mining is a tactical process that uses mathematical algorithms to sift through large data-stores to extract data patterns/models/rules The Knowledge Discovery is the process of identifying and understanding potentially useful hidden anomalies, trends and patterns. Data mining is an integral part of knowledge discovery process

4. Data Mining and Statistics ? DM sounds very similar to regression analysis but its approach and purpose are quite different –Statistical methods tests a hypothesis on a data set –Data Mining starts from the data sets to construct a hypothesis

5. Data Mining - Present State Application Domains

6. Data Mining Methodologies 1.Business Understanding 2.Data Understanding 3.Data Preparation 4.Modeling 5.Evaluation 6.Deployment SIX STEPS PROCESS

7. Visualization Use human pattern recognition capabilities Statistics Applying statistical techniques to predict Decision Trees Building scripts based on historic data Association Rules (Rule Induction) Reasoning from specific facts to reach a hypothesis Clustering Refers to finding and visualizing groups of facts that were not previously known Neural Networks Learning how to solve problems based on examples K-Nearest Neighbor Classification by looking at similar data Genetic Algorithms Survival of the fittest … TECHNIQUESTECHNIQUES USAGEUSAGE Discover Understand Predict Data Mining Technology

8. What is ERP? ERP is a solution, which facilitates company-wide integrated information systems, covering all functional areas performs core Corporate activities and increases customer service augmenting Corporate Image.

9. Why ERP? For Management – to know what is happening in the company One solution for better Management For cycle time reduction To achieve cost control & low working capital To marry latest technologies To shun the geographical gaps To satisfy the customers with high expectations To be Competitive & for survival

10. ERP - Definition “Software solution that addresses the Enterprise needs, taking a process view of the overall organization to meet the goals, by tightly integrating all functions and under a common software platform”

11. Enterprise Applications Landscape ERP Solutions –Oracle –PeopleSoft –SAP ERP vendors have extended scope of their applications far beyond tradition ERP functions to a wide array of business solutions. Oracle Business Intelligence Solution Peoplesoft Enterprise Performance Management SAP Business Information Warehouse

12. Oracle Business Intelligence Solution Business Processes (Pre-Built Portlets) Response to Lead (27) Lead to Quote (56) Quote to Order (15) Order to Cash (34) Demand to Build (40) Procure to Pay (28) Revenue to Compensation (29) Expiration to Renewal (33) Issue to Resolution (51) HR Family (43) Oracle 9i DM Integration Oracle Marketing Online for Campaign Management Oracle9iAS Personalization iStore more to come… Oracle9iDS Warehouse Builder Oracle9iAS Discoverer Oracle9iDS Reports Oracle9iAS Portal Oracle9iAS Clickstream Intelligence Oracle9iAS Personalization Oracle9i Data Mining Oracle9iDS Business Intelligence Beans Oracle 9i Business Intelligence

13. SAP Business Intelligence Solution SAP CRM –Campaign management –Opportunity analytics –Customer behavior modeling SAP SCM –Demand planning –Speed optimization Closed loop platform capabilities Drill-through (report-report i/f) Remote cubes (read through) Real-time data warehousing Data mining Write back to operational system SAP Portals E-commerce analysis SAP Markets, Procurement Bidding, pattern-based offering Activity reproting, service analytics Business Information Warehouse

14. ERPs and Data Mining: Good and the Bad News Good News –Known Business Processes –Few data Sources –Improved Data Quality –Near real-time data mining –Closed-loop Knowledge Discovery Bad News –Complex Data Structures –Performance –Availability –Very few Data Mining algorithms - Today

15. Thank You