Is It Safe to Paste SQL Queries Into ChatGPT? What You Need to Know

-- BEFORE (risky — reveals business logic and real customer values):
SELECT
    u.customer_id,
    u.churn_risk_score,
    u.annual_recurring_revenue,
    COUNT(o.order_id) AS order_count,
    MAX(o.created_at) AS last_order_date
FROM customers u
LEFT JOIN subscription_orders o
    ON u.customer_id = o.customer_id
    AND o.status = 'completed'
WHERE u.churn_risk_score > 0.7
    AND u.email = 'alice@realcompany.com'
    AND u.contract_end_date BETWEEN '2024-01-01' AND '2024-06-30'
GROUP BY u.customer_id, u.churn_risk_score, u.annual_recurring_revenue
HAVING COUNT(o.order_id) < 3
ORDER BY u.churn_risk_score DESC;

-- AFTER (safe — anonymized but structurally identical):
SELECT
    u.user_id,
    u.score_a,
    u.metric_b,
    COUNT(o.item_id) AS count_c,
    MAX(o.created_at) AS latest_date
FROM table_a u
LEFT JOIN table_b o
    ON u.user_id = o.user_id
    AND o.status = 'completed'
WHERE u.score_a > 0.7
    AND u.identifier = 'example@example.com'
    AND u.date_field BETWEEN '2024-01-01' AND '2024-06-30'
GROUP BY u.user_id, u.score_a, u.metric_b
HAVING COUNT(o.item_id) < 3
ORDER BY u.score_a DESC;

-- The AI helps with the query logic, JOINs, and optimization.
-- You substitute your real names back afterward.

# Run SQLCoder locally with Ollama — zero data leaves your machine
# All inference happens on your local GPU or CPU

# Step 1: Install Ollama (Mac/Linux)
curl -fsSL https://ollama.ai/install.sh | sh

# Step 2: Pull the SQLCoder model (fine-tuned for SQL generation)
ollama pull sqlcoder:7b
# Or the larger, more capable version:
ollama pull sqlcoder:15b

# Step 3: Use SQLCoder for schema-aware SQL generation
ollama run sqlcoder:7b

# Example prompt to SQLCoder:
# "Given this schema:
# CREATE TABLE orders (id INT, customer_id INT, amount DECIMAL, status VARCHAR);
# CREATE TABLE customers (id INT, email VARCHAR, tier VARCHAR);
# Write a query to find customers with more than 5 orders in the last 30 days."

# SQLCoder generates accurate SQL with no data leaving your network
# Ideal for: enterprise environments, healthcare data, financial data