Data Preparation

The Data Quality can vary a lot and influences algorithm qualities. Thus we need to clean and integrate data:

• Data Cleaning

• Data Migration

• Data Integration

• Correlation Analysis

• Data Reduction

  • Dimensionality Reduction
  • Numerosity Reduction
  • Data Compression

• Data Transformation

  • Feature Generation
  • Aggregationstypen auf MDMs
  • Normalization

• Data Discretization

  • Binning
  • Histogram Analysis
  • Clustering

• Concept-Hierarchy Generation