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Overview

Brighthive uses DBT Cloud (integrated via Datapiary) for data transformations. The platform’s DBT Agent can generate transformation models from natural language descriptions and submit them as GitHub pull requests — giving your team full control over what gets deployed.

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How It Works

  1. Describe what you need — Tell BrightAgent what transformation you want in plain English.
  2. DBT Agent generates the model — Creates SQL transformations with proper dbt structure, configurations, and tests.
  3. GitHub PR submitted — All generated code goes through a pull request for human review.
  4. Team reviews and approves — Nothing gets deployed without your approval.
  5. DBT Cloud executes — Approved models run on DBT Cloud, executing transformations in your Redshift warehouse.
  6. Neo4j tracks lineage — Transformation relationships are recorded in the knowledge graph.

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DBT Cloud Integration

Managed via Datapiary

DBT Cloud is integrated through the Datapiary library, providing a consistent interface for transformation management.

Runs in Redshift

dbt models execute in your workspace’s dedicated Redshift Serverless cluster.

Version Controlled

All dbt models live in Git — full history, branching, and code review via GitHub PRs.

Lineage in Neo4j

Neo4j tracks dependencies between source tables, staging layers, and data marts — visible in the data catalog.

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What Neo4j Tracks

Neo4j serves as the control plane for transformations, maintaining visibility across:
  • Source tables — Raw data from organizations.
  • Staging layers — Cleaned and standardized intermediate tables.
  • Data marts — Final analytical tables ready for consumption.
  • Dependencies — Which models depend on which sources and other models.
  • Run history — When transformations last ran and their status.