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Selects and configures optimal incremental model strategies
---
name: incremental-model-strategy-selector-5e1b820b71bf
description: Selects and configures optimal incremental model strategies
version: 1.0.0
category: Transformation
skillId: SK-DEA-019
allowed-tools:
- Read
- Write
- Edit
- Glob
- Grep
- Bash
graph:
domains: [domain:data-engineering]
specializations: [specialization:data-engineering-analytics]
skillAreas: [skill-area:dbt-modeling, skill-area:etl-pipelines]
roles: [role:analytics-engineer, role:data-engineer]
workflows: [workflow:data-pipeline-deployment]
---
# 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
1. Analyze source data update patterns
2. Measure data volume and update frequency
3. Select strategy based on characteristics
4. 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
---
name: incremental-model-strategy-selector-5e1b820b71bf
description: Selects and configures optimal incremental model strategies
version: 1.0.0
category: Transformation
skillId: SK-DEA-019
allowed-tools:
- Read
- Write
- Edit
- Glob
- Grep
- Bash
graph:
domains: [domain:data-engineering]
specializations: [specialization:data-engineering-analytics]
skillAreas: [skill-area:dbt-modeling, skill-area:etl-pipelines]
roles: [role:analytics-engineer, role:data-engineer]
workflows: [workflow:data-pipeline-deployment]
---
# 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
1. Analyze source data update patterns
2. Measure data volume and update frequency
3. Select strategy based on characteristics
4. 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
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.