Data analysis tools help professionals find insights from data sets. Tools are essential for making informed decisions and predictions. Data analysis tools are software programs for interpreting and visualizing data
Data mining discovers actionable information from large datasets using mathematical analysis. Mining models can be applied for forecasting, risk assessment, recommendations, and grouping. Process includes six basic steps: problem definition, data preparation, exploration, modeling, validation, and deployment
Parallel option enables real-time and batch processing of Oracle Data Mining functions. Parallel settings can be enabled/disabled using ALTER SESSION commands. Degree of parallelism can be adjusted for better performance
Advisor framework privileges are part of DBA role. SQL Tuning Set management available through DBMS_SQLTUNE package. SQL Profile management deprecated, replaced by SQL Management Object
WOE measures predictive power of independent variable relative to dependent variable. Evolved from credit scoring, separates good from bad customers. Calculated as natural logarithm of non-event/event percentages. Requires splitting data into 10-20 bins with minimum 5% observations
Data mining analyzes large data sets to identify patterns and extract useful information. Process includes data collection, warehousing, organization, and analysis. Data mining follows six-step process: understand business, prepare data, build model, evaluate results, implement change