SQL for Finance Data

Financial databases are large, structured, and relational, multiple tables linked together by common keys (company ID, period, instrument identifier). SQL (Structured Query Language) is the universal language for querying these databases efficiently. Whether you're using Bloomberg's BQUANT, a Prowess database, an internal data warehouse, or a Supabase/PostgreSQL database you've built yourself, SQL is the tool.

For a finance professional, SQL proficiency means the ability to slice, aggregate, filter, and join financial data at scale, extracting exactly the numbers you need rather than downloading everything and filtering in Excel. It also means you can write queries that others can read, understand, and audit, creating reproducible analysis.

SQL is not a programming language per se, it's a declarative query language. You describe what data you want; the database engine figures out how to fetch it. The learning curve is gentler than Python, making it one of the highest ROI skills for a financial analyst.

Core SQL for financial analysis:

SELECT and filtering:

SELECT company_name, revenue, ebitda_margin, fy
FROM financials
WHERE sector = 'Pharmaceuticals'
  AND fy BETWEEN 2020 AND 2025
  AND revenue > 5000  -- ₹ Crore
ORDER BY revenue DESC;

Aggregations:

SELECT sector,
       AVG(ebitda_margin) AS avg_margin,
       COUNT(*) AS company_count
FROM financials
WHERE fy = 2024
GROUP BY sector
HAVING COUNT(*) >= 5
ORDER BY avg_margin DESC;

JOINs (linking tables):

SELECT c.company_name, f.revenue, f.pat, p.pe_ratio
FROM companies c
JOIN financials f ON c.id = f.company_id AND f.fy = 2024
JOIN price_multiples p ON c.id = p.company_id;

Window functions (YoY growth, running totals):

SELECT company_name, fy, revenue,
       revenue / LAG(revenue) OVER (PARTITION BY company_id ORDER BY fy) - 1
         AS revenue_growth_yoy
FROM financials
ORDER BY company_id, fy;

CTEs (Common Table Expressions) for readable multi-step queries:

WITH sector_avg AS (
  SELECT sector, AVG(roe) AS avg_roe FROM financials WHERE fy=2024 GROUP BY sector
)
SELECT f.company_name, f.roe, s.avg_roe,
       f.roe - s.avg_roe AS roe_premium
FROM financials f
JOIN sector_avg s ON f.sector = s.sector
WHERE f.fy = 2024;