Data foundation / GenAI ETL pipeline building

Build the path from raw data to useful insight.

Bring data together faster with AI-assisted ingestion and transformation across files, systems, warehouses, and other business sources.

For data engineers, developers and analytics teams.

Source data flowing into a preparation checklist
Product in contextSource data flowing into a preparation checklist
Product workflow
Inputs
  • Files & systems
  • Warehouse sources
  • Transformation requirements
ProductGenAI ETL pipeline building
Output

Prepared data for analytics and reporting

What your team can do

GenAI ETL
in your workflow.

AI-assisted preparation

Use AI assistance to describe ingestion and transformation work instead of starting every pipeline from a blank page.

Connected source workflows

Bring files, systems and warehouses into the preparation workflow with explicit source and transformation context.

Reviewable pipeline steps

Review the proposed work and how the data is prepared before using it downstream.

How the work connects

From requirements
to a reviewed result.

  1. 01

    Describe

    Specify the source data and the output your team needs.

  2. 02

    Plan

    Review the proposed ingestion and transformation steps.

  3. 03

    Prepare

    Apply the agreed preparation workflow.

  4. 04

    Validate

    Check the resulting data before it feeds analytics.

Start with your requirements.

Discuss source access, shared definitions, output requirements and review responsibilities before planning an implementation. The workflow above is an overview, not a live product session.

Business applications

Explore the context
behind the use case.

Frequently asked questions

Plan the next step.

Who is this product for?

Data engineers, developers and analytics teams working on genai etl and its surrounding data workflow.

What should we bring to a discussion?

Bring your files & systems, warehouse sources, transformation requirements, a representative business question and the review requirements your team needs to meet.

How can we explore the wider platform?

Visit the product overview for the connected product map and reference-data ontology model, or talk to our team about your specific workflow.

Discuss GenAI ETL

Your workflow.
The right starting point.

Share your data sources, users and output requirements so we can discuss how this product fits.

Talk to Our Team