1. Chapter 8 Business Intelligence & ERP
ERP offers opportunity to store vast volumes of data
This data can be data mined
Customer Relationship Management

2. Data Storage Systems Data Warehousing CRM one data mining application
Orderly & accessible repository of known facts & related data
Subject-oriented, integrated, time-variant, non-volatile
Massive data storage
Efficient data retrieval
CRM one data mining application
Can use all of this data
Common ERP add-on

3. Granularity Definition – level of detail
Most granular – each transaction stored
Averaging & aggregation loses granularity
Data warehouses usually store data at fine levels of granularity
You can’t undo averages & aggregates

4. Data Marts Different definitions Small version of data warehouse
Temporary storage of data
possibly from multiple sources
for a specific study

5. On-Line Analytic Processing
OLAP
Multidimensional databases
Display data on selected dimensions
Time
Region
Product
Department
Customer
Etc.

6. Data Quality Problem causes Data corrupted or missing
Failure of software transferring data into or out of data warehouse
Failure of data cleansing process

7. Data Integrity No meaningless, corrupt, or redundant data
Part of data warehousing function to clean data
Data standardization
Remove ambiguity (different ways to abbreviate)
Matching
Associating variables (unique mapping)

8. Database Product Comparison
Use
Duration
Granularity
Data warehouse
Repository
Permanent
Finest
Data mart
Specific study
Temporary
Aggregate
OLAP
Report & Analysis
Repetitive
Summary

9. Data Mining Analysis of large quantities of data by computer
Micromarketing
Versatile
Apply to a wide variety of models
Scalable
Can analyze very large data sets

10. Types of data mining Hypothesis Testing Knowledge Discovery
Traditional statistics
Knowledge Discovery
No predetermined expectation of relationships

11. Business Data Mining Applications
Area
Applications
Retailing
Market basket analysis, cross-sell
Banking
Customer relationship mgmt
Credit Card Mgmt
Lift, churn
Insurance
Fraud detection
Telecommunications
Churn (customer turnover)
Telemarketing
On-line caller information
Human Resource Mgmt
Churn (employee turnover)

12. Customer Relationship Management
Determine value of customer
Identify what they want
Package products (services) to keep them
Maximize expected net present value of customer

13. Summary Customer Relationship Management very promising
Has not reached all expectations as ERP add-on
Quite expensive to get needed data storage capability
Still an opportunity to use all the data generated by an ERP