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+# **SQL for Forex Data Analysis: The 20% That Delivers 80% Results**
+
+## **Focused Learning Roadmap**  
+*Master these core skills to handle most forex data analysis tasks*
+
+### **Phase 1: Core Skills (Week 1-2)**  
+**What to Learn** | **Why It Matters** | **Key Syntax Examples**
+-----------------|-------------------|----------------------
+**Filtering Data** | Isolate specific currency pairs/timeframes | `SELECT * FROM ticks WHERE symbol='EUR/USD' AND timestamp > '2023-01-01'`
+**Time Bucketing** | Convert raw ticks into candlesticks (1min/5min/1H) | `DATE_TRUNC('hour', timestamp) AS hour`
+**Basic Aggregates** | Calculate spreads, highs/lows, averages | `AVG(ask-bid) AS avg_spread`, `MAX(ask) AS high`
+**Grouping** | Summarize data by pair/time period | `GROUP BY symbol, DATE_TRUNC('day', timestamp)`
+
+---
+
+### **Phase 2: Essential Techniques (Week 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 currency pairs (e.g., EUR/USD vs. USD/JPY) | `CORR(eurusd_mid, usdjpy_mid)`
+**Session Analysis** | Compare volatility across trading sessions | `WHERE EXTRACT(HOUR FROM timestamp) IN (7,13,21)` *(London/NY/Asia hours)*
+
+---
+
+### **Phase 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)`
+
+---
+
+## **10 Essential Forex Queries You'll Use Daily**  
+1. **Current Spread Analysis**  
+   ```sql
+   SELECT symbol, AVG(ask-bid) AS spread 
+   FROM ticks 
+   WHERE timestamp > NOW() - INTERVAL '1 hour'
+   GROUP BY symbol;
+   ```
+
+2. **5-Minute Candlesticks**  
+   ```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 Comparison**  
+   ```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**  
+- **Week 1**: Master `SELECT`, `WHERE`, `GROUP BY`, `DATE_TRUNC`  
+  → *Goal: Generate hourly OHLC data for one currency pair*  
+- **Week 2**: Learn `JOIN`, `AVG() OVER()`, `CORR()`  
+  → *Goal: Compare two pairs' correlation over different timeframes*  
+- **Week 3**: Optimize with indexes + CTEs  
+  → *Goal: Run a 1M-row query in <1 second*  
+
+---
+
+## **Tools to Start With**  
+- **Data**: Free forex ticks from [Dukascopy](https://www.dukascopy.com/)  
+- **Database**: DuckDB (lightweight, no setup required)  
+- **Visualization**: Metabase (free) or Python with Matplotlib  
+
+---
+
+## **What to Avoid (For Now)**  
+- Stored procedures  
+- Advanced indexing strategies  
+- Machine learning in SQL  
+- Recursive queries  
+
+---
+
+### **Bare Minimum Survival Kit**  
+1. `WHERE` + `DATE_TRUNC` *(filter and bucket time data)*  
+2. `GROUP BY` *(summarize data efficiently)*  
+3. `AVG() OVER()` *(rolling calculations)*  
+4. `CORR()` *(measure pair relationships)*  
+
+**Next Step**: Want a 5-question quiz to test your core knowledge? Or shall we dive deeper into one technique?
+
+---
+
 Understood! You're seeking **maximum SQL mastery with minimum time investment** by focusing on the critical 20% that delivers 80% of results in forex data analysis. Here's your **laser-focused SQL SME blueprint**:
 
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