1. Oracle大数据工作流
2. Oracle库内分析架构
3. Oracle MoviePlex商店应用程序的界面 （这些元素在现在的腾讯视频应用中都有）
4. 词频分析可视化（标签云）
5. 数据挖掘及统计技术的应用场景
| Sample Problem | Type of Problem | Algorithm | Applicability |
| Predict customer response to a marketing campaign | Classification（分类） | 1. Logistic Regression (GLM) 2. Decision Trees 3. Naïve Bayes 4. Support Vector Machine | 1. Classical statistical technique Embedded within an application 2. Wide/narrow data/text |
| Predict the likely profitability of a new customer | Regression（回归） | 1. Multiple Regression (GLM) 2. Support Vector Machine | |
| Given customer response to a marketing campaign program, find the most significant predictors | Attribute Importance（属性重要性） | Minimum Description Length (MDL) | 1. Attribute reduction 2. Identify useful data 3. Reduce data noise |
| Identify customer purchasing behavior that is significantly different from the norm | Anomaly Detection（异常检测） | One Class SVM | Quality control |
| Find the items that tend to be purchased together and specify their relationship— market basket analysis | Association Rules（关联规则） | A priori | Product grouping |
| Segment data into clusters and rank the probability that an individual will belong to a given cluster | Clustering（聚合） | 1. Hierarchical K-Means 2. Hierarchical O-Means | 1. Product grouping 2. Text mining 3. Gene analysis |
| Combining attributes into a new reduced set of features | Feature Extraction（特征提取） | Non-negative Matrix Factorization (NMF) | 1. Text analysis 2. Feature reduction |
6. Data mining extension for SQL Developer
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