Data AnalyticsBeginner12 min readUpdated March 2025

SQL for Data Analysis

SQL is the analyst’s everyday tool for pulling answers out of databases. Learn the query building blocks — SELECT, WHERE, GROUP BY and ORDER BY — through realistic business questions.

The Shape of an Analytics Query

Most analysis questions reduce to: *filter some rows, group them, aggregate a measure, and sort the result.* SQL expresses each step with a clause:

SELECT — Choose columns and calculated measures.
FROM — The table (or joined tables) to read.
WHERE — Filter individual rows before grouping.
GROUP BY — Collapse rows into groups.
HAVING — Filter groups after aggregation.
ORDER BY / LIMIT — Sort and cap the output.

Answering a Business Question

*"Which product categories earned the most revenue in 2024, excluding cancelled orders?"*

sql

SELECT
    p.category,
    COUNT(DISTINCT o.order_id)          AS orders,
    SUM(oi.quantity * oi.unit_price)    AS revenue,
    ROUND(AVG(oi.unit_price), 2)        AS avg_price
FROM orders o
JOIN order_items oi ON oi.order_id = o.order_id
JOIN products p     ON p.product_id = oi.product_id
WHERE o.status <> 'cancelled'
  AND o.order_date >= '2024-01-01'
  AND o.order_date <  '2025-01-01'
GROUP BY p.category
HAVING SUM(oi.quantity * oi.unit_price) > 10000
ORDER BY revenue DESC
LIMIT 10;

Handling NULLs and Dates

Real data has gaps. Use `COALESCE` to supply defaults and date functions to bucket time:

sql

SELECT
    DATE_TRUNC('month', order_date)         AS month,
    COALESCE(region, 'Unknown')             AS region,
    COUNT(*)                                AS orders,
    SUM(total_amount)                       AS revenue
FROM orders
WHERE order_date >= CURRENT_DATE - INTERVAL '12 months'
GROUP BY 1, 2
ORDER BY 1, 2;

Habits of Good Analysts

Reliable numbers come from careful habits:

Check row counts after every join to catch accidental duplication.
Use explicit date ranges (>= start and < end) instead of BETWEEN for timestamps.
Alias every calculated column with a clear name.
Sanity-check totals against a known source before sharing.

Key Takeaways

Most questions are filter, group, aggregate, sort.
WHERE filters rows; HAVING filters groups.
Use COALESCE for NULLs and DATE_TRUNC for time buckets.
Always validate row counts and totals after joins.

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