# Database Views Summary

## Overview
Updated the public schema with new views to make advertising analytics data from Meta, Google, and combined sources more accessible.

## Changes Made

### 1. Adapted `explore_schemas.py` Script
- Modified to save schema exploration output to `schema_info.txt`
- Provides persistent reference for table structures across meta, google, and alpinebits schemas
- Usage: `uv run explore_schemas.py`

### 2. New Views Added

#### **account_insights_by_country** ✓
- Aggregates Meta campaign insights by country to account level
- **Columns**: time, account_id, country, impressions, clicks, spend, link_click, landing_page_view, lead
- **Purpose**: Analyze Meta advertising performance by geographic region
- **Source**: meta.custom_campaign_country

#### **g_campaign_insights** ✓
- Google campaign-level insights with calculated performance metrics
- **Columns**: time, campaign_id, campaign_name, clicks, impressions, interactions, cost_micros, cost, conversions, all_conversions, conversions_value, ctr, cpm, cpc, cost_per_conversion
- **Purpose**: Unified Google campaign performance view with key metrics (CTR, CPM, CPC, Cost per Conversion)
- **Source**: google.campaign_metrics

#### **unified_account_insights_by_device** ✓
- Combines Meta and Google account insights broken down by device type
- **Columns**: time, google_account_id, meta_account_id, device, google_impressions, meta_impressions, total_impressions, google_clicks, meta_clicks, total_clicks, google_cost, meta_spend, total_spend, meta_link_clicks, meta_leads
- **Purpose**: Compare Meta vs Google performance by device (DESKTOP, MOBILE, TABLET)
- **Requires**: account_metadata table for linking Meta and Google accounts

#### **unified_account_insights_by_gender** ✓
- Meta audience insights broken down by gender
- **Columns**: time, meta_account_id, gender, impressions, clicks, spend, link_clicks, leads
- **Purpose**: Analyze Meta advertising performance by audience gender demographics
- **Source**: meta account_insights_by_gender

### 3. Existing Views (Not Modified)
The following views were already present and working correctly:
- **campaign_insights** - Base Meta campaign insights
- **campaign_insights_by_gender/age/device/country** - Meta campaign breakdowns
- **account_insights** - Aggregated Meta account insights
- **account_insights_by_gender/age/device/gender_and_age** - Meta account breakdowns
- **ads_insights** (materialized) - Individual ad performance
- **adset_insights** - Ad set level insights
- **g_account_insights** - Google account-level insights
- **g_account_insights_device** - Google account insights by device
- **unified_account_insights** - Combined Meta+Google account-level view

## Testing
All views have been tested and verified to:
- Execute without errors
- Return valid data with correct column structures
- Support LIMIT queries for performance verification

## Usage Examples

```sql
-- View Meta performance by country
SELECT time, country, SUM(impressions), SUM(spend), SUM(lead)
FROM account_insights_by_country
WHERE account_id = '1416908162571377'
GROUP BY time, country;

-- View Google campaign metrics
SELECT time, campaign_name, clicks, impressions, cpc, cpm
FROM g_campaign_insights
WHERE ctr > 2.0
ORDER BY time DESC
LIMIT 10;

-- Compare device performance across Meta and Google
SELECT time, device, total_impressions, total_clicks, total_spend
FROM unified_account_insights_by_device
ORDER BY time DESC;

-- Analyze Meta audience by gender
SELECT time, gender, impressions, clicks, spend, leads
FROM unified_account_insights_by_gender
WHERE time > CURRENT_DATE - INTERVAL '30 days'
ORDER BY time, gender;
```

## Next Steps
- Set up automated refreshes for materialized views if needed
- Create additional unified views for campaign-level comparisons
- Consider indexing frequently queried views for performance optimization