Data Transformation

Team Studio provides operators to clean and prepare data for use before modeling.

For example, some operators do not allow null values, so you might need to clean your data set by removing null or missing values. Your data might include data points that lie outside of the threshold for your consideration, so you might want to replace these outliers.

• Aggregation Methods for Batch Aggregation
  In contrast to the Aggregation operator, which forces you to configure each aggregation separately, with the Batch Aggregation operator, you can select many numeric columns for each aggregation method and computes all these aggregations at once. The result is a wide dataset that contains the grouping column and a column for each of the aggregations.
• Outliers in Numerical Data
  Your numerical data might include data that lies outside of a specified percentile threshold.
• Creating a Join condition for a database join.
  You can perform a join on two tables using the Join operator.
• Key-Value Pairs Parsing Example using the Variable Operator
  You can use the Variable operator to parse data fields that are stored in a key-value pair format, such as JSON, dictionaries, and database STRUCT formats.
• datetime Format Conversion Examples
  You can use the Variable operator to convert datetime formats.

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