Skip to content


The RandomCentury transformer is crafted to populate specified database columns with random century values. It is ideal for applications that require historical data simulation, such as generating random years within specific centuries for historical databases, testing datasets with temporal dimensions, or anonymizing dates in historical research data.


Name Description Default Required Supported DB types
column The name of the column to be affected Yes text, varchar
keep_null Indicates whether NULL values should be preserved false No -


The RandomCentury transformer utilizes an algorithm or a library function (hypothetical in this context) to generate random century values. Each value represents a century (e.g., 19th, 20th, 21st), providing a broad temporal range that can be used to enhance datasets requiring a distribution across different historical periods without the need for precise date information.

Example: Populate random centuries for the historical_artifacts table

This example shows how to configure the RandomCentury transformer to populate the century column in a historical_artifacts table with random century values, adding an element of variability and historical context to the dataset.

RandomCentury transformer example
- schema: "public"
  name: "historical_artifacts"
    - name: "RandomCentury"
        column: "century"
        keep_null: false

In this setup, the century column will be filled with random century values, replacing any existing non-NULL values. If the keep_null parameter is set to true, then existing NULL values in the column will remain untouched, preserving the original dataset's integrity where no temporal data is available.