Data Transformation

Shape your ingested data into analysis-ready datasets without writing complex pipelines.

DataStori's Data Transformation lets you turn the raw data landing in your destination into clean, business-ready tables. Once your sources are connected and data is flowing, you can:

• Define a data model to describe your business entities, metrics, and relationships in one consistent place, so everyone works from the same definitions.
• Build transformations using AI Builder use our AI Builder to build transformations. Customize or extend it for your use case.
• Standardize and enrich data across multiple sources, resolving differences in structure and naming into a unified view.
• Keep outputs fresh by running transformations on a schedule alongside your ingestion pipelines.

Explore the sections below to get started.

📄️ Data Model

The data model is where you describe your data so that DataStori — and your team — share a single, consistent understanding of it. Behind the scenes, the model is captured as an ontology YAML, which the AI Builder uses to generate transformations. You can work with the data model through an interactive UI or by editing the YAML directly.

📄️ AI Builder

The AI Builder is an AI agent that turns a plain-language goal into a working transformation. You describe what you want to do, and the agent reads your data model, figures out the relevant tables and relationships, and produces a PySpark script along with a clear explanation of what the script does.