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Tool guide
dbt (Data Build Tool)
Defines source-backed analytics engineering and data transformation, evidence handling, and action boundaries.
Read the fileOverview
dbt (Data Build Tool) overview
Use this bundle to structure analytics engineering and data transformation while keeping official-source context separate from account, organization, project, document, or environment.
Read the fileWorkflow
dbt (Data Build Tool) source-backed triage
1. State the requested decision or deliverable. 2. Inventory evidence: dbt product and version, project, packages, adapter, profile, and target, models, sources, seeds, snapshots, macros.
Read the fileTemplate
dbt transformation and review brief
Review-ready brief for analytics engineering and data transformation, evidence quality, verification, and controlled next actions.
Read the fileIs this bundle right for your task?
Who it is for
- People who configure, operate, integrate, govern, or review work performed in dbt (Data Build Tool)
- Teams working in Data and analytics, Software
When to use it
- A proposed dbt (Data Build Tool) configuration or workflow change needs current IDs, permissions, dependencies, tests, and rollback evidence.
- A report, export, integration, or automation result needs to be reconciled against actual workspace state and current product documentation.
What you need to provide
- The product version or workspace scope, relevant configuration or export, desired outcome, permissions, and accountable owner.
- Current IDs, settings, records, logs, screenshots, integration details, and test evidence needed to verify the requested change.
Tasks and expected outputs
Questions it helps answer
- Prepare a dbt transformation and review brief without fabricating local facts.
- Separate verified, provided, assumed, and missing evidence.
- Produce review-ready decisions with explicit verification and approval boundaries.
What it helps produce
- dbt transformation and review brief
Practical example
Use it with an agent
Load the bundle as context, provide the evidence named above, then adapt this example to your situation.
Provide the product version or workspace scope, relevant configuration or export, desired outcome, permissions, and accountable owner. Ask the agent to review dbt (Data Build Tool) and produce dbt transformation and review brief that maps configuration evidence, dependencies, permissions, tests, rollback, and actions that still require approval. Begin with docs.getdbt.com, then confirm that the reference is current and applicable. Inspect dbt (Data Build Tool) before drafting.
Context path: bundles/tools/dbt
What the bundle includes
Tools
- dbt (Data Build Tool)
Frameworks
- source-evidence matrix
- analytics-engineering-and-data-transformation evidence matrix
- qualified-review gate
Evaluations
- dbt (Data Build Tool) source verification check
Sources used to build this bundle
These are the public references behind the role definition and operating guidance. The bundle does not replace current documentation or evidence from your site.
Limitations and safe use
Do not use this for
- Changing live configuration, records, permissions, automations, integrations, or shared data without verified scope, testing, rollback, and approval.
Known limitations
- Use official dbt (Data Build Tool) sources for general context; local analytics engineering and data transformation, configuration, records, values, states, and permissions require inspected evidence.
- Task-specific work requires current evidence for dbt product and version, project, packages, adapter, profile, and target, models, sources, seeds, snapshots, macros, and exposures, properties, contracts, tests, and documentation, selection syntax and invocation parameters, manifest, run results, catalog, logs, and lineage, and warehouse permissions, deployment, and approval evidence.
- Do not infer project structure, models, sources, tests, lineage, target, run status, warehouse state.
Safety notes
- Minimize personal, customer, employee, financial, credential, and other sensitive data.
- Require explicit confirmation before running production jobs, changing models or contracts, modifying targets, deploying packages, or altering warehouse objects.
- Route legal, privacy, security, compliance, financial, employment, and other qualified judgments to accountable reviewers.