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Key Characteristics of Static Columns

  • Immutable: Values in static columns do not change unless updated manually.
  • Minimal Configuration: Requires only a name, data type, and dataset reference during creation.
  • No Computation Required: Unlike dynamic columns, static columns do not process data or call external services.

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Why Use Static Column

  • Manual Data Entry: Static columns are ideal for storing user-provided values that do not change frequently. Users can input and update information manually without the need for automated processing.
  • Fixed Categorical Data: When datasets contain categorical values such as labels, predefined categories, or classifications, static columns help in maintaining a structured format without requiring additional computation.
  • Initial Data Setup: When setting up a dataset, static columns can be used to pre-fill rows with default values. This ensures that every entry in the dataset follows a consistent structure and prevents missing or null values from appearing in newly added rows.

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Supported Data Types:

Static Columns support the following data types:
  • text
  • array
  • json
  • image
  • audio
  • float
  • integer
  • boolean
  • datetime
Static columns provide a simple, reliable way to store structured data without needing complex processing. They are best suited for cases where values remain constant and do not require computation, making them an essential building block in data management.