Advanced Usage

Project Health Configuration

You can configure the project health settings by providing a configuration file. The configuration file is a YAML file that contains the following fields:

version: v1

# Insights to disable
disabled_insights:
  - source_staging_model_integrity
  - downstream_source_dependence
  - Duplicate_Sources
  - hard_coded_references
  - rejoining_upstream_concepts
  - model_fanout
  - multiple_sources_joined

# Define patterns to identify different types of models
model_type_patterns:
  staging: "^stg_.*"       # Regex for staging models
  mart: "^(mrt_|mart_|fct_|dim_).*"  # Regex for mart models
  intermediate: "^int_.*"  # Regex for intermediate models
  base: "^base_.*"         # Regex for base models

# Configure insights
insights:
  # Set minimum test coverage percent and severity for 'Low Test Coverage in DBT Models'
  dbt_low_test_coverage:
    min_test_coverage_percent: 30
    severity: WARNING

  # Configure maximum fanout for 'Model Fanout Analysis'
  model_fanout.max_fanout: 10

  # Configure maximum fanout for 'Source Fanout Analysis'
  source_fanout.max_fanout: 10

  # Define model types considered as downstream for 'Staging Models Dependency Check'
  staging_models_dependency.downstream_model_types:
    - mart

Key Sections of the config file

disabled_insights: Insights that you want to disable
model_type_patterns: Regex patterns to identify different model types like staging, mart, etc.
insights: Custom configurations for each insight. For each insight, you can set specific thresholds, severity levels, or other parameters.

Severity can have 3 values -> INFO, WARNING, ERROR

Overriding default configs for the insights

To change the severity level or set a threshold, modify the corresponding insight under the insights section. For example:

insights:
  dbt_low_test_coverage:
    severity: WARNING

For insights with more complex configurations (like fanout thresholds or model types), you need to specify the insight name and corresponding parameter under insights. For example:

insights:
  model_fanout.max_fanout: 10