data mining and erp presented by: abhineet malviya ankesh jindal mayur shinde
TRANSCRIPT
Data Mining and ERP
Presented by: Abhineet Malviya
Ankesh JindalMayur Shinde
Agenda
• Data Mining and Knowledge Discovery Basics
• ERP Vendors and Data Mining Solutions
• Pro and Cons of ERP centric Data Mining
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
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
Data Mining - Present State
Business 317 73%Life Sciences 85 20%Other 31 7%
Application Domains
Data Mining Methodologies
1. Business Understanding
2. Data Understanding
3. Data Preparation
4. Modeling
5. Evaluation
6. Deployment
SIX STEPS PROCESS
VisualizationUse human pattern recognition capabilities
StatisticsApplying statistical techniques to predict
Decision TreesBuilding scripts based on historic data
Association Rules (Rule Induction)Reasoning from specific facts to reach a hypothesis
ClusteringRefers to finding and visualizing groups of facts that were not previously known
Neural NetworksLearning how to solve problems based on examples
K-Nearest NeighborClassification by looking at similar data
Genetic Algorithms
Survival of the fittest …
TECHNIQUES
TECHNIQUES
USAGE
USAGE
Discover
Understand
Predict
Data Mining Technology
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.
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
ERP - Definition
“Software solution that addresses theEnterprise needs, taking a process view ofthe overall organization to meet the goals,by tightly integrating all functions andunder a common software platform”
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
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
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
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
Thank You