feat: migrate transform to 3-layer architecture with per-layer schemas

Remove raw/ layer — staging models now read landing JSON directly.
Rename all model schemas from padelnomics.* to staging.*/foundation.*/serving.*.
Web app queries updated to serving.planner_defaults via SERVING_DUCKDB_PATH.
Supervisor gets daily sleep interval between pipeline runs.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

web/src/padelnomics/analytics.py

@@ -7,7 +7,7 @@ All queries run via asyncio.to_thread() to avoid blocking the event loop.
 Usage:
     from .analytics import fetch_analytics
 
-    rows = await fetch_analytics("SELECT * FROM padelnomics.planner_defaults WHERE city_slug = ?", ["berlin"])
+    rows = await fetch_analytics("SELECT * FROM serving.planner_defaults WHERE city_slug = ?", ["berlin"])
 """
 import asyncio
 import os
@@ -17,7 +17,7 @@ from typing import Any
 import duckdb
 
 _conn: duckdb.DuckDBPyConnection | None = None
-_DUCKDB_PATH = os.environ.get("DUCKDB_PATH", "data/lakehouse.duckdb")
+_DUCKDB_PATH = os.environ.get("SERVING_DUCKDB_PATH", "data/analytics.duckdb")
 
 
 def open_analytics_db() -> None:

web/src/padelnomics/planner/routes.py

@@ -603,7 +603,7 @@ async def market_data():
     from ..analytics import fetch_analytics
 
     rows = await fetch_analytics(
-        "SELECT * FROM padelnomics.planner_defaults WHERE city_slug = ? LIMIT 1",
+        "SELECT * FROM serving.planner_defaults WHERE city_slug = ? LIMIT 1",
         [city_slug],
     )
     if not rows:

web/src/padelnomics/scripts/refresh_from_daas.py

@@ -1,7 +1,7 @@
 """
 Refresh template_data rows from DuckDB analytics serving layer.
 
-Reads per-city market data from the `padelnomics.planner_defaults` serving table
+Reads per-city market data from the `serving.planner_defaults` serving table
 and overwrites matching static values in `template_data.data_json`.  This keeps
 article financial model inputs in sync with the real-world data pipeline output.
 
@@ -81,7 +81,7 @@ def _load_analytics(city_slugs: list[str]) -> dict[str, dict]:
         conn = duckdb.connect(str(path), read_only=True)
         placeholders = ", ".join(["?"] * len(city_slugs))
         rows = conn.execute(
-            f"SELECT * FROM padelnomics.planner_defaults WHERE city_slug IN ({placeholders})",
+            f"SELECT * FROM serving.planner_defaults WHERE city_slug IN ({placeholders})",
             city_slugs,
         ).fetchall()
         cols = [d[0] for d in conn.description]