DATASET_NORMALIZE_WORKERS
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.. _datasetnormalizeworkers:



DATASET_NORMALIZE_FIT Worker 
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Overview
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A new worker, ``DATASET_NORMALIZE_FIT``, has been added to Workflows.

This worker standardizes numeric dataset columns using available (non-missing) values and generates the normalization parameters required for consistent data preprocessing. The resulting parameters can be used by downstream normalization and inverse-normalization workflows.

Key Features
------------

- Added support for the ``DATASET_NORMALIZE_FIT`` worker in Workflows
- Standardizes numeric dataset columns using non-missing values
- Computes and stores normalization parameters
- Supports consistent dataset preprocessing across workflows
- Integrates with normalization and inverse-normalization processes


.. thumbnail:: /_images/Images/datasetnormalizefitworker.png
   :title:

   DATASET_NORMALIZE_FIT

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DATASET_NORMALIZE_APPLY Worker 
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Overview
--------

A new worker, ``DATASET_NORMALIZE_APPLY``, is now available in Workflows.

This worker standardizes numeric dataset columns using normalization parameters generated by the ``DATASET_NORMALIZE_FIT`` worker. By applying previously calculated mean and standard deviation values, the worker ensures consistent normalization across datasets without recalculating the normalization parameters.

Key Features
------------

- Added support for the ``DATASET_NORMALIZE_APPLY`` worker in Workflows
- Standardizes numeric dataset columns using precomputed normalization parameters
- Uses mean and standard deviation values generated by ``DATASET_NORMALIZE_FIT``
- Ensures consistent normalization across multiple datasets
- Supports machine learning and analytics preprocessing workflows


.. thumbnail:: /_images/Images/datasetnormalizenormalizeworker.png
   :title:

   DATASET_NORMALIZE_APPLY

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DATASET_NORMALIZE_INVERSE Worker
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Overview
--------

A new worker, ``DATASET_NORMALIZE_INVERSE``, is now available in Workflows.

This worker reverses a previously applied normalization transformation, restoring normalized numeric dataset columns back to their original scale using the normalization parameters generated by the ``DATASET_NORMALIZE_FIT`` worker.

The worker is particularly useful for converting model outputs, predictions, or transformed datasets back into their original units for interpretation, reporting, and downstream processing.

Key Features
------------

- Added support for the ``DATASET_NORMALIZE_INVERSE`` worker in Workflows
- Restores normalized numeric columns to their original scale
- Uses normalization parameters generated by ``DATASET_NORMALIZE_FIT``
- Supports inverse transformation without recalculating parameters
- Integrates seamlessly with normalization workflows

.. thumbnail:: /_images/Images/datasetnormalizinverseworker.png
   :title:

   DATASET_NORMALIZE_INVERSE

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