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