SQL & Queries

Essential SQL SELECT, WHERE, and GROUP BY for Spreadsheet Analysts

October 7, 2026 · By editorial

skills.efektifpro.com – As corporate databases swell beyond Excel’s 1,048,576 row ceiling, spreadsheet analysts inevitably face a transition to Structured Query Language (SQL). Fortunately, if you already understand Excel filters, formulas, and Pivot Tables, you already grasp 80% of SQL’s conceptual logic. SQL simply applies those same analytical operations directly inside the database warehouse.

⚡ The Mental Rosetta Stone: Excel to SQL Mapping

SELECT = Choosing which columns to view.
WHERE = Applying AutoFilter dropdowns to raw rows.
GROUP BY = Dragging fields into Pivot Table “Rows”.
SUM() / COUNT() = Dragging fields into Pivot Table “Values”.
HAVING = Value Filter on aggregated Pivot Table results.
ORDER BY = Sorting your spreadsheet output A-Z or Z-A.

Core Query Structure

Every analytical SQL query follows an intuitive narrative flow:

SELECT 
    region,
    category,
    COUNT(order_id) AS total_orders,
    SUM(revenue) AS total_revenue,
    ROUND(AVG(revenue), 2) AS average_order_value
FROM sales_transactions
WHERE status = 'Completed' 
  AND transaction_date >= '2026-01-01'
GROUP BY region, category
HAVING SUM(revenue) > 50000
ORDER BY total_revenue DESC;

Demystifying WHERE vs. HAVING

The single most confusing concept for spreadsheet analysts entering SQL is distinguishing between WHERE and HAVING. Both act as filters, but they operate at different stages of calculation:

Filter Clause	When it Evaluates	Excel Analogy
`WHERE`	BEFORE aggregation occurs. Filters raw individual rows in the table.	Filtering raw records in your table before building a Pivot Table.
`HAVING`	AFTER aggregation occurs. Filters aggregated group summaries.	Applying a “Value Filter” to Pivot Table grand totals (e.g., show only teams over $50k).

Pro Tip: Dealing with NULL vs Empty Strings

In Excel, a blank cell is often treated interchangeably with zero or empty text "". In SQL databases, NULL represents the total absence of data. Testing WHERE customer_id = NULL will always fail; you must write WHERE customer_id IS NULL or WHERE customer_id IS NOT NULL to properly isolate empty fields.

🏷️ Topics:

#Data Cleaning #SQL Analytics