No-code Transformations

A visual transformation layer that lets you clean, reshape, and enrich data without writing code or scripts.

The no-code transformations module in Dataworkz lets you manipulate and shape data using a visual interface. You configure transformation rules by selecting operations, fields, and parameters — Dataworkz generates and executes the underlying logic automatically. This enables faster data preparation and makes transformation accessible to both technical and non-technical users.

Transformation Approaches

Two approaches are available:

• Transform with AI — Describe the transformation you want in plain language. Dataworkz interprets the description and applies the operation automatically. Best suited for filters, sorts, and aggregations.

• Actions menu — Select from a full catalogue of operations directly. Use this for precise, complex, or multi-parameter transformations.

Both approaches record every step applied in the Steps panel, giving you a full audit trail and the ability to reorder or remove individual steps.

Features

Feature	Description
Visual interface	Configure transformation rules by selecting operations and parameters — no code required.
50+ built-in functions	Pre-built operations covering filtering, aggregation, masking, hashing, deduplication, joins, case statements, window functions, and AI-powered enrichment.
Column-level transformations	Apply operations to individual columns — format, calculate, mask, hash, copy, convert, or look up values — with type-specific options based on the column's data type.
Data type support	Transformations are available for String, Numeric, Boolean, Date, and Datetime/Timestamp columns.
Real-time preview	The Dataset view updates immediately after each transformation so you can validate the output before executing.
Lineage tracking	Every transformation is automatically recorded. The full sequence is visible in the Steps panel and persisted in the Dataset's lineage.
Reusable Dataflows	Save a transformation sequence as a Dataflow and apply it to other Datasets using Import from Dataflow.