1. Example
1.1. KFC/Pizza Hut
1.1.1. Zap Business Intelligence
1.1.1.1. improve market optimization and customer service,dynamic pricing
1.2. Jaeger
1.2.1. LossManager
1.2.1.1. Prevent fraud transactions and unauthorized discounts
2. Softwares
2.1. IBM SPSS
2.2. Clementine
2.3. Cognos 8
2.4. SAS Enterprise Miner
2.5. SQL Server Analysis
2.6. Surfaid Analytics
2.7. PowerPivot
2.8. Waikato Environment for Knowledge Analysis
2.9. RapidMiner
2.10. KNIME
3. Challenges
3.1. Technological
3.1.1. Need large infrastructure and Software limitations
3.2. Ethical
3.2.1. Privacy
3.3. Legislative
3.3.1. Data quality
4. Use
4.1. Competative Advantage
4.1.1. Market Research
4.1.1.1. Element of market dominace
4.1.2. Risk Management
4.1.2.1. Bankruptcy prediction, Better investment
4.1.3. Manifacturing Optimization
4.1.3.1. Shipment, Material usage, Scheduling
4.2. Customers’ Relationships
4.2.1. Customer Targeting
4.2.1.1. Target customer with right product.
4.2.2. Customer satisfaction
4.2.2.1. Reasons and the cost of swiching,chum,and satisfactory level
4.2.3. Market baskets
4.2.3.1. Marketing and Advertisement
4.2.4. Pricing Discrimination
4.2.4.1. Dynamic pricing
4.3. Logistics and Inventory Management
4.3.1. Production managment
4.3.1.1. Prevent overproduction and underproduction
4.3.2. Sheduling supply chain
4.3.2.1. Dynamically manage the supplies
4.3.3. Forecasting
4.3.3.1. Forecasting the demand for production
4.4. Anomalies and Fraud Detection
4.4.1. Fraud detection
4.4.1.1. Detect fraudulence transaction, Find hacker,fraudsters
4.4.2. Anomalies detection
4.4.2.1. Find why anomalies happened and avoid them
5. Tools
5.1. Data mining
5.2. Text mining
5.3. Web mining
5.3.1. Type
5.3.1.1. Web content mining
5.3.1.1.1. Discover and extract information from Web documents and services.
5.3.1.2. Web structure mining
5.3.1.2.1. Discovers the structure of the hyperlinks between documents.
5.3.1.3. Web usage mining
5.3.1.3.1. Discover usage patterns from Web data.