Incremental Model Strategy Selector
Overview
Selects and configures optimal incremental model strategies. This skill optimizes data transformation efficiency through proper incremental processing patterns.
Capabilities
- •Incremental strategy selection (append, merge, delete+insert)
- •Partition pruning optimization
- •Unique key configuration
- •On_schema_change handling
- •Full refresh scheduling
- •Lookback window optimization
- •Late-arriving data handling
Input Schema
json
{
"modelCharacteristics": {
"sourceType": "string",
"updatePattern": "append|update|delete",
"volumeGB": "number",
"updateFrequency": "string"
},
"platform": "snowflake|bigquery|redshift",
"existingModel": "object"
}
Output Schema
json
{
"strategy": "append|merge|delete+insert",
"config": "object",
"partitionStrategy": "object",
"refreshSchedule": "object",
"dbtConfig": "object"
}
Target Processes
- •Incremental Model Setup
- •dbt Model Development
- •Pipeline Migration
Usage Guidelines
- •Analyze source data update patterns
- •Measure data volume and update frequency
- •Select strategy based on characteristics
- •Configure appropriate lookback windows
Best Practices
- •Use append for insert-only sources
- •Use merge for sources with updates
- •Configure partition pruning for large tables
- •Schedule periodic full refreshes for data correction
- •Handle late-arriving data with appropriate lookback