Data preparation is the process of cleaning and transforming raw data into organized data so that it can be processed and analyzed further. In data preparation, data is reformatted, corrected, and combined to enrich the data.
Data preparation is complex yet essential to create contextual data, so that the analysis of such data may prove efficient to produce reliable and insightful results. In the absence of preparation, biased data may result in poor analysis and erroneous results.
Notes:

• The Reader (Dataset) should be connected to the algorithm.
  • These algorithms can be used only on numerical data.
• You can use one algorithm after the other for preparing your data.

List of Data Preparation Algorithms

• Aggregation
• Combined Data Cleansing
• Data Joiner
• Data Merge
• Data Pivot
• Data Unpivot
• Descriptive Statistics
• Expression
• Factor Analysis
• File Management
• Filtering
• Lookup
• Missing Value Imputation
• Outlier Detection
• Sequence Generator
• Sorting