Snowflake Reliability Patterns
Implement Snowflake reliability patterns: replication, failover, Time
4,653,104 AI resources indexedWorking toward the world’s largest AI resource index.
dbt (data build tool) patterns for data transformation and analytics engineering. Use when building data models, implementing data quality tests, or managing data transformation pipelines.
---
name: dbt-4b3a579b8e1c
description: dbt (data build tool) patterns for data transformation and analytics engineering. Use when building data models, implementing data quality tests, or managing data transformation pipelines.
user-invocable: false
---
# dbt Skill
This skill provides dbt patterns for analytics engineering.
## Project Structure
```
dbt_project/
├── dbt_project.yml
├── models/
│ ├── staging/
│ │ └── stg_customers.sql
│ ├── intermediate/
│ │ └── int_customer_orders.sql
│ └── marts/
│ └── fct_orders.sql
├── seeds/
├── macros/
├── tests/
└── snapshots/
```
## Model Patterns
### Staging Models
```sql
-- models/staging/stg_customers.sql
with source as (
select * from {{ source('raw', 'customers') }}
),
renamed as (
select
id as customer_id,
lower(email) as email,
created_at
from source
)
select * from renamed
```
### Incremental Models
```sql
-- models/marts/fct_orders.sql
{{
config(
materialized='incremental',
unique_key='order_id'
)
}}
select *
from {{ ref('stg_orders') }}
{% if is_incremental() %}
where updated_at > (select max(updated_at) from {{ this }})
{% endif %}
```
## Testing
```yaml
# models/schema.yml
models:
- name: stg_customers
columns:
- name: customer_id
tests:
- unique
- not_null
- name: email
tests:
- unique
```
## Best Practices
- Use staging → intermediate → marts pattern
- Source all raw data with `source()`
- Reference models with `ref()`
- Add documentation and tests
- Use incremental models for large datasets
---
name: dbt-4b3a579b8e1c
description: dbt (data build tool) patterns for data transformation and analytics engineering. Use when building data models, implementing data quality tests, or managing data transformation pipelines.
user-invocable: false
---
# dbt Skill
This skill provides dbt patterns for analytics engineering.
## Project Structure
```
dbt_project/
├── dbt_project.yml
├── models/
│ ├── staging/
│ │ └── stg_customers.sql
│ ├── intermediate/
│ │ └── int_customer_orders.sql
│ └── marts/
│ └── fct_orders.sql
├── seeds/
├── macros/
├── tests/
└── snapshots/
```
## Model Patterns
### Staging Models
```sql
-- models/staging/stg_customers.sql
with source as (
select * from {{ source('raw', 'customers') }}
),
renamed as (
select
id as customer_id,
lower(email) as email,
created_at
from source
)
select * from renamed
```
### Incremental Models
```sql
-- models/marts/fct_orders.sql
{{
config(
materialized='incremental',
unique_key='order_id'
)
}}
select *
from {{ ref('stg_orders') }}
{% if is_incremental() %}
where updated_at > (select max(updated_at) from {{ this }})
{% endif %}
```
## Testing
```yaml
# models/schema.yml
models:
- name: stg_customers
columns:
- name: customer_id
tests:
- unique
- not_null
- name: email
tests:
- unique
```
## Best Practices
- Use staging → intermediate → marts pattern
- Source all raw data with `source()`
- Reference models with `ref()`
- Add documentation and tests
- Use incremental models for large datasets
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.