Dbt Incremental Strategy Audit

Purpose

Determine whether a dbt incremental model's chosen strategy is justified, understandable, maintainable, and consistent with repository conventions. The goal is not to praise clever implementations. Default stance: skeptical, low-risk, root-cause oriented, convention-preserving — prefer the simplest correct strategy.

When to Use

• Reviewing a new or modified materialized='incremental' model
• An incremental model shows confusing runtime behavior: unexpected rebuilds, deletes, or reprocessing
• A model deviates from the repo's established incremental conventions without explanation

Inputs

• The model SQL and its config: incremental_strategy, unique_key, partition_by/cluster_by/partitions, pre_hook/post_hook
• Comparable incremental models in the same repo

Workflow

1. Understand the repo pattern first. Inspect similar incremental models and how they configure their strategies:

   grep -rn "incremental_strategy" models/
   grep -rln "is_incremental()" models/
   

2. Explain the actual runtime behavior. Compile the model and read the SQL that really runs — is_incremental() branches make the Jinja source misleading:

   dbt compile --select <model>
   # then read target/compiled/<project>/models/.../<model>.sql
   

   is_incremental() is false when the target table does not yet exist or on --full-refresh, so reason through both branches.

3. Review the full incremental surface: materialized='incremental', incremental_strategy, is_incremental() logic, unique_key, partition_by/cluster_by/partitions, pre_hook/post_hook, delete/overwrite/merge semantics, rolling window logic, deduplication choices.

4. Identify hidden risks:

   • hybrid full-refresh behavior hidden inside an incremental model
   • deletes outside expected scope
   • reprocessing more data than intended
   • partition/window drift and maintenance burden
   • strategy mismatch with the repo's established conventions
   • operational complexity without clear business benefit
   • confusing runtime behavior that future maintainers may misread

5. Check downstream stability before recommending a change:

   dbt ls --select <model>+
   

   Strategy changes can shift BI/reporting outputs; list affected downstream assets.

Output

• A. Current model runtime behavior
• B. Repo convention comparison
• C. Strategy risks
• D. Whether the complexity is justified
• E. Safer alternative
• F. Minimal-diff recommendation
• G. Validation plan

Verification

• Compiled SQL inspected, not just the Jinja source
• At least one comparable incremental model in the repo compared
• Delete/overwrite/merge scope stated explicitly
• Downstream assets listed before any strategy change is recommended
• Recommendation is a minimal diff and includes a validation plan

Failure Modes

• Praising cleverness — operational complexity without clear business benefit is a finding, not a feature.
• Reading Jinja instead of compiled SQL — is_incremental() branches hide the real runtime behavior.
• Auditing in isolation — a strategy that is fine on its own may still be an unjustified deviation from repo conventions.