deepline-analyticslisted

# Deepline Analytics Use this skill to answer customer analytics questions through Deepline's warehouse and semantic-layer tools. The goal is not just to run SQL; it is to preserve the customer's business definitions by starting from the semantic layer, validating the query path, and reporting exactly what metric definitions and filters were used. ## Before You Start Use `deepline-gtm` instead when the task is prospecting, enrichment, contact finding, outbound sequencing, personalization, or row-by-row lead/account research. Analytics questions ask about existing customer data: revenue, pipeline, funnel, conversion, retention, usage, calls, accounts, opportunities, or warehouse tables. If Snowflake credentials or a semantic layer are missing, stop and report the setup blocker. Guessing table names or falling straight to raw SQL hides the actual problem and usually produces incorrect business definitions. ## Decision Matrix | User asks... | Job | Start with | | --- | --- | --- | | "What is total pipeline by quarter?" | Metric breakdown | `snowflake_get_semantic_layer`, then `snowflake_run_semantic_query` | | "Break revenue down by product/month" | Dimensional analysis | Inspect semantic tables for revenue metrics and time dimensions | | "How many opportunities / accounts / calls..." | Simple count metric | Find the semantic count metric before writing SQL | | "Why does this number look wrong?" | Debug/validation | Run semantic query, inspect returned SQL, then compare wi