Chapter 11: Business Intelligence and Knowledge Management
Chapter 11: Business Intelligence and Knowledge Management
Data Mining and Online Analysis * Data warehouses are useless without software tools * Process data into information * Business intelligence (BI): information gleaned with information tools
Data Mining * Data mining: selecting, exploring, and modeling data * * Supports decision making * Finds relationships and ratios within data * Finds unknown relationships * * Queries are more complex than traditional * Combination of data-warehouse and data-mining facilitates predictions * Data mining has four objectives * * Sequence or path analysis * Classification * Clustering * Forecasting * * Techniques applied to various fields * * Marketing * Fraud detection * Marketing to individual * * Data mining can predict customer behavior * Banking * * Find profitable customers * Find patterns of fraud * * Mobile phones * Customers tend to switch companies often * Customer loyalty programs ensure steady flow of customer data
Potential Applications of Data Mining Data Mining Application | Description | Consumer clustering | Identify the common characteristics of consumers who tend to buy the same products and services from your company. | Costumer churn | Identify the reason customers switch to competitors; predict which customers are likely to do so. | Fraud detection | Identify characteristics of transactions that are most likely to be fraudulent. | Direct marketing | Identify which prospective clients should be included in a mailing or e – mail list to obtain the highest response rate. | Interactive marketing | Predict what each individual accessing a web site is most likely to be interested in seeing. | Market basket analysis | Understand what products or services are commonly
Data Mining and Online Analysis * Data warehouses are useless without software tools * Process data into information * Business intelligence (BI): information gleaned with information tools
Data Mining * Data mining: selecting, exploring, and modeling data * * Supports decision making * Finds relationships and ratios within data * Finds unknown relationships * * Queries are more complex than traditional * Combination of data-warehouse and data-mining facilitates predictions * Data mining has four objectives * * Sequence or path analysis * Classification * Clustering * Forecasting * * Techniques applied to various fields * * Marketing * Fraud detection * Marketing to individual * * Data mining can predict customer behavior * Banking * * Find profitable customers * Find patterns of fraud * * Mobile phones * Customers tend to switch companies often * Customer loyalty programs ensure steady flow of customer data
Potential Applications of Data Mining Data Mining Application | Description | Consumer clustering | Identify the common characteristics of consumers who tend to buy the same products and services from your company. | Costumer churn | Identify the reason customers switch to competitors; predict which customers are likely to do so. | Fraud detection | Identify characteristics of transactions that are most likely to be fraudulent. | Direct marketing | Identify which prospective clients should be included in a mailing or e – mail list to obtain the highest response rate. | Interactive marketing | Predict what each individual accessing a web site is most likely to be interested in seeing. | Market basket analysis | Understand what products or services are commonly