Here's a streamlined 8-week roadmap focused purely on practical SQL skills for forex bid/ask analysis, structured for immediate application in cron jobs:

### **Week 1-2: Core Foundations for Tick Data**
**Goal:** Process raw ticks into usable formats  
**Key Skills:**
1. **Basic filtering**  
   ```sql
   -- Isolate specific currency pairs/time windows
   SELECT * FROM ticks 
   WHERE symbol = 'EUR/USD' 
     AND timestamp BETWEEN '2024-01-01 00:00' AND '2024-01-01 23:59'
   ```

2. **Candlestick generation**  
   ```sql
   -- 1-minute OHLC candles
   SELECT 
     symbol,
     DATE_TRUNC('minute', timestamp) AS minute,
     FIRST(bid) AS open,
     MAX(bid) AS high,
     MIN(bid) AS low,
     LAST(bid) AS close
   FROM ticks
   GROUP BY symbol, minute
   ```

3. **Spread metrics**  
   ```sql
   -- Average spread by hour
   SELECT 
     symbol,
     EXTRACT(HOUR FROM timestamp) AS hour,
     AVG(ask - bid) AS avg_spread
   FROM ticks
   GROUP BY symbol, hour
   ```

### **Week 3-4: Session Analysis & Basic Signals**
**Goal:** Identify trading opportunities  
**Key Skills:**
1. **Session volatility**  
   ```sql
   -- London vs. NY session comparison
   SELECT 
     CASE 
       WHEN EXTRACT(HOUR FROM timestamp) BETWEEN 7 AND 15 THEN 'London'
       WHEN EXTRACT(HOUR FROM timestamp) BETWEEN 13 AND 21 THEN 'NY'
       ELSE 'Other' 
     END AS session,
     STDDEV((bid+ask)/2) AS volatility
   FROM ticks
   GROUP BY session
   ```

2. **Rolling spreads**  
   ```sql
   -- 30-minute moving spread
   SELECT 
     timestamp,
     AVG(ask - bid) OVER (
       ORDER BY timestamp 
       ROWS BETWEEN 29 PRECEDING AND CURRENT ROW
     ) AS rolling_spread
   FROM ticks
   WHERE symbol = 'GBP/USD'
   ```

3. **Basic alerts**  
   ```sql
   -- Spread widening alert
   SELECT symbol, timestamp, (ask - bid) AS spread
   FROM ticks
   WHERE (ask - bid) > 3 * (
     SELECT AVG(ask - bid) 
     FROM ticks 
     WHERE timestamp > NOW() - INTERVAL '1 day'
   )
   ```

### **Week 5-6: Advanced Pattern Detection**
**Goal:** Build automated signal detectors  
**Key Skills:**
1. **Microprice calculation**  
   ```sql
   -- Weighted mid-price
   SELECT 
     timestamp,
     (bid*ask_size + ask*bid_size)/(bid_size + ask_size) AS microprice
   FROM ticks
   ```

2. **Order flow imbalance**  
   ```sql
   -- Bid/ask size ratio
   SELECT 
     timestamp,
     (bid_size - ask_size)/(bid_size + ask_size) AS imbalance
   FROM ticks
   WHERE ABS((bid_size - ask_size)/(bid_size + ask_size)) > 0.7
   ```

3. **Consecutive moves**  
   ```sql
   -- 5+ consecutive bid increases
   WITH changes AS (
     SELECT *,
       CASE WHEN bid > LAG(bid) OVER (ORDER BY timestamp) THEN 1 ELSE 0 END AS is_up
     FROM ticks
   )
   SELECT timestamp, bid
   FROM changes
   WHERE is_up = 1
   ORDER BY timestamp
   LIMIT 5
   ```

### **Week 7-8: Optimization & Productionization**
**Goal:** Make scripts robust and efficient  
**Key Skills:**
1. **Indexing for time-series**  
   ```sql
   CREATE INDEX idx_symbol_time ON ticks(symbol, timestamp);
   ```

2. **CTEs for complex logic**  
   ```sql
   WITH 
   london_ticks AS (
     SELECT * FROM ticks 
     WHERE EXTRACT(HOUR FROM timestamp) BETWEEN 7 AND 15
   ),
   spreads AS (
     SELECT symbol, AVG(ask - bid) AS avg_spread
     FROM london_ticks
     GROUP BY symbol
   )
   SELECT * FROM spreads WHERE avg_spread > 0.0005;
   ```

3. **Partitioning large tables**  
   ```sql
   CREATE TABLE ticks_partitioned (
     -- schema
   ) PARTITION BY RANGE (timestamp);
   ```

### **Daily Practice Structure**
1. **Morning (5 min):** Run basic monitoring query  
   ```sql
   -- Current spread status
   SELECT symbol, AVG(ask - bid) AS spread 
   FROM ticks 
   WHERE timestamp > NOW() - INTERVAL '15 minutes'
   GROUP BY symbol;
   ```

2. **Evening (15 min):** Build one new analysis query  
   - Monday: Session comparisons  
   - Tuesday: Rolling metrics  
   - Wednesday: Alert conditions  
   - Thursday: Optimization tweaks  
   - Friday: Backtest old queries  

### **Key Mindset Shifts**
1. **Think in ticks, not hours:** Your queries should process milliseconds efficiently  
2. **Pre-compute everything:** Generate candlesticks/aggregates in SQL, not Python  
3. **Log everything:** Every cron job should write results to a logging table  

Want the condensed 1-page cheat sheet version of this roadmap? Or should we focus next on building your first complete cron-ready SQL script?