For Developers

Build pipelines, model data, run compute, and operate the platform — for data engineers, analytics engineers, ML engineers, and platform admins.

Start here

1. Quick Start — sign up and open your workspace.
2. Platform Overview — how DataNature is put together.
3. Data Engineering — ingest, transform, and promote data through the medallion layers.

What you can do

Goal	Read
Understand the architecture	Architecture
Store and query data	Data Warehouse, SQL Workbench, Tables
Define business metrics	Semantic Layer (Cubes)
Build and schedule pipelines	Data Engineering, Ingestion, Transformation (dbt), Jobs, Pipeline Scheduling
Run notebooks and Spark jobs	Notebooks & Workbench, Apache Spark, Using Notebooks & Spark
Use an operational Postgres	Lakebase (Postgres)
Train models and build agents	Machine Learning, Agent Meta-Harness
Govern and secure data	Governance, Atlas, Access & Policies
Fix an error	Troubleshooting, Limits & Known Issues
Move from another platform	Migration

Looking for dashboards and conversational analytics instead? See the Business User docs.