Define and modify metrics in the Lightdash semantic layer using dbt YAML syntax.
npx skills add https://github.com/yu-iskw/dbt-heros --skill edit-metrics
Please help me install this Agent Skill. Skill: Edit Metrics Source: https://github.com/yu-iskw/dbt-heros/tree/main/plugins/lightdash-development/skills/edit-metrics Command: npx skills add https://github.com/yu-iskw/dbt-heros --skill edit-metrics
This Skill streamlines the process of defining and updating metrics within the Lightdash semantic layer, ensuring consistency and accuracy in data calculations.
references/basics.md and references/advanced.md for correct syntax and advanced configurations.total_revenue metric for the orders model by summing the amount column, referencing references/basics.md for the correct type: sum syntax.Use the edit metrics skill to define a new metric named 'average_order_value' by averaging the 'order_total' column in the 'orders' model.
High-intent search queries and answers about installing and using this skill.
To define Lightdash metrics, you write dbt YAML configurations specifying aggregation types like sum or average. This ensures consistent calculations directly within your dbt models using the 1.10+ standards.
Yes, you can modify Lightdash metrics with advanced configurations like filters and groups. The skill references advanced syntax patterns to apply these granular controls to your dbt models.
The correct dbt YAML syntax for aggregated calculations involves defining the metric type, such as type: sum, at the column or model level. This skill uses reference files to ensure accurate dbt 1.10+ compliance.
Yes, the Lightdash semantic layer supports atomic aggregations at both the column and model levels. This allows you to define metrics like total revenue by summing specific columns directly.
You update an existing metric by modifying its dbt YAML definition within your semantic layer. The skill ensures these modifications adhere to Fusion standards and references advanced configuration syntax.
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juandaniel190Answer natural language business questions by querying dbt data models.