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

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

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

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

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

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

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)

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

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

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

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)

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

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