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+Here’s the **20% of SQL skills that will deliver 80% of your forex data analysis needs**, structured as a focused roadmap:
+
+---
+
+### **SQL for Forex Data: The 20% Priority Roadmap**
+#### **1. Core Skills (Weeks 1-2)**
+| Skill | Why It Matters | Key Syntax |
+|-------|---------------|------------|
+| **Filtering Data** | Isolate specific currency pairs/timeframes | `SELECT * FROM ticks WHERE symbol='EUR/USD' AND timestamp > '2023-01-01'` |
+| **Time Bucketing** | Convert ticks to candles (1min/5min/1H) | `DATE_TRUNC('hour', timestamp) AS hour` |
+| **Basic Aggregates** | Calculate spreads, averages, highs/lows | `AVG(ask-bid) AS avg_spread`, `MAX(ask) AS high` |
+| **Grouping** | Summarize by pair/time period | `GROUP BY symbol, DATE_TRUNC('day', timestamp)` |
+
+#### **2. Essential Techniques (Weeks 3-4)**
+| Skill | Forex Application | Example |
+|-------|-------------------|---------|
+| **Joins** | Combine tick data with economic calendars | `JOIN economic_events ON ticks.date = events.date` |
+| **Rolling Windows** | Calculate moving averages/volatility | `AVG(price) OVER (ORDER BY timestamp ROWS 30 PRECEDING)` |
+| **Correlations** | Compare pairs (EUR/USD vs. USD/JPY) | `CORR(eurusd_mid, usdjpy_mid)` |
+| **Session Analysis** | Compare London/NY/Asia volatility | `WHERE EXTRACT(HOUR FROM timestamp) IN (7,13,21)` |
+
+#### **3. Optimization (Week 5)**
+| Skill | Impact | Implementation |
+|-------|--------|----------------|
+| **Indexing** | Speed up time/symbol queries | `CREATE INDEX idx_symbol_time ON ticks(symbol, timestamp)` |
+| **CTEs** | Break complex queries into steps | `WITH filtered AS (...) SELECT * FROM filtered` |
+| **Partitioning** | Faster queries on large datasets | `PARTITION BY RANGE (timestamp)` |
+
+---
+
+### **Prioritized Cheat Sheet**
+#### **10 Queries You’ll Use Daily**
+1. **Current Spread**:  
+   ```sql
+   SELECT symbol, AVG(ask-bid) AS spread 
+   FROM ticks 
+   WHERE timestamp > NOW() - INTERVAL '1 hour'
+   GROUP BY symbol;
+   ```
+
+2. **5-Min Candles**:  
+   ```sql
+   SELECT 
+     DATE_TRUNC('5 minutes', timestamp) AS time,
+     MIN(bid) AS low,
+     MAX(ask) AS high
+   FROM ticks
+   WHERE symbol = 'GBP/USD'
+   GROUP BY time;
+   ```
+
+3. **Rolling Volatility**:  
+   ```sql
+   SELECT 
+     timestamp,
+     STDDEV(ask) OVER (ORDER BY timestamp ROWS 100 PRECEDING) AS vol
+   FROM ticks
+   WHERE symbol = 'EUR/USD';
+   ```
+
+4. **Session Volume**:  
+   ```sql
+   SELECT 
+     CASE 
+       WHEN EXTRACT(HOUR FROM timestamp) BETWEEN 7 AND 15 THEN 'London' 
+       ELSE 'Other' 
+     END AS session,
+     SUM(volume) AS total_volume
+   FROM ticks
+   GROUP BY session;
+   ```
+
+---
+
+### **Study Plan**
+1. **Week 1**: Master `SELECT`, `WHERE`, `GROUP BY`, `DATE_TRUNC`  
+   → *Goal: Generate hourly high/low/close for 1 pair*
+
+2. **Week 2**: Learn `JOIN`, `AVG() OVER()`, `CORR()`  
+   → *Goal: Compare 2 pairs’ correlation last week vs. last month*
+
+3. **Week 3**: Optimize with indexes + CTEs  
+   → *Goal: Make a 1M-row query run in <1 sec*
+
+---
+
+### **Tools to Use Now**
+- **Data**: Free forex ticks from [Dukascopy](https://www.dukascopy.com/)  
+- **Database**: DuckDB (simple, fast, no setup)  
+- **Visualization**: Metabase (free) or Python’s Matplotlib
+
+---
+
+### **Avoid Until Later**
+- Stored procedures  
+- Advanced indexing strategies  
+- Machine learning in SQL  
+- Recursive queries  
+
+---
+
+**Key Principle**: Focus on **time-based analysis** (the core of forex data) first. Everything else builds on this.  
+
+Want the absolute bare minimum? Learn these 4 things:  
+1. `WHERE` + `DATE_TRUNC` (filter and bucket time)  
+2. `GROUP BY` (summarize data)  
+3. `AVG() OVER()` (rolling calculations)  
+4. `CORR()` (pair relationships)  
+
+Would you like a 5-question quiz to test your 20% knowledge?
+
+---
+
 Here's a structured **Technical Guide & Roadmap for Forex Tick Data Analysis with SQL**, designed as a progressive learning path with clear milestones and reference examples:
 
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