Guides

Excel vs SQL: Term-by-Term Mapping with Side-by-Side Examples

By Ravindra Bagale, Excel & Data Analytics trainer · LinkedIn · Published: 7 October 2026 · Last updated: 7 October 2026

Raja Coffee Roasters keeps its orders in an Excel table. The owner asks Shraddha, the analyst: "What did Pune buy?" A SQL user types SELECT SUM(Amount) FROM Orders WHERE City = 'Pune';. An Excel user types =SUMIFS(Orders[Amount],Orders[City],"Pune"). Both get ₹10,700. The two tools ask the same questions in different words. Learn the word pairs and you can move between them.

SQL and Excel answer the same questions. WHERE is a filter or the condition part of SUMIFS and FILTER; GROUP BY is a PivotTable or SUMIFS by category (GROUPBY in Microsoft 365); JOIN is XLOOKUP or Power Query Merge; ORDER BY is SORT; DISTINCT is UNIQUE; CASE WHEN is IF or IFS. Use Excel for quick, visual analysis of data that fits in a sheet, and SQL when the data lives in a database or is too big for a sheet.

Download the practice file (vs-sql.xlsx)

Excel file, 12 KB. It has the sample data used below. All numbers in this workbook are fictional teaching data, not real company figures.

The term-mapping table

Read across each row: the SQL clause, the Excel menu way, and the Excel formula way.

Side-by-side examples

All examples use the same Orders table (24 orders) and Customers table (7 customers) in the practice file. We ran every SQL query in SQLite on the same rows and checked that Excel returns the same answer.

GROUP BY and HAVING

-- SQL
SELECT City, SUM(Amount) AS Sales, COUNT(*) AS Orders
FROM Orders
GROUP BY City
HAVING SUM(Amount) > 5000;

' Excel (one row per city)
Sales   =SUMIFS(Orders[Amount],Orders[City],A14)
Orders  =COUNTIFS(Orders[City],A14)
HAVING  =FILTER(A14:A18,B14:B18>5000)

Cities with sales above ₹5,000: Nagpur, Pune, Solapur. In a PivotTable, the same HAVING is Row Labels > Value Filters > Greater Than. In Microsoft 365 you can also write =GROUPBY(Orders[City],Orders[Amount],SUM).

JOIN = XLOOKUP (and Power Query Merge)

A LEFT JOIN keeps every order and brings the customer's segment when there is a match. XLOOKUP does the same, one row at a time:

-- SQL
SELECT o.OrderID, c.Segment
FROM Orders o LEFT JOIN Customers c ON o.Customer = c.Customer;

' Excel, in a new column of Orders
=XLOOKUP(C2,Customers[Customer],Customers[Segment],"(no match)")

Ruhi is in Orders but not in Customers. SQL returns NULL for her segment; the XLOOKUP returns "(no match)" because we gave it that as the fourth argument. An INNER JOIN would keep only the 22 orders that match. For joins on many columns or large tables, use Data > Get Data > Combine Queries > Merge in Power Query and pick the join kind (Left Outer, Inner, Full Outer and so on).

WHERE that returns rows, ORDER BY and LIMIT

-- SQL
SELECT OrderID FROM Orders WHERE City = 'Pune' AND Amount >= 1000;
SELECT Amount FROM Orders ORDER BY Amount DESC LIMIT 3;

' Excel
=FILTER(Orders[Order ID],(Orders[City]="Pune")*(Orders[Amount]>=1000))
=LARGE(Orders[Amount],1)   then 2 and 3
=TAKE(SORT(Orders[Amount],,-1),3)   (Microsoft 365)

The FILTER returns orders 1006, 1011, 1012, 1020, 1021, 1024. Multiplying the two conditions means AND; adding them means OR. The three largest orders are ₹3,200, ₹2,100, ₹1,920.

CASE WHEN and window functions

-- SQL
SELECT OrderID,
  CASE WHEN Amount >= 1500 THEN 'Large' WHEN Amount >= 800 THEN 'Medium' ELSE 'Small' END AS Size,
  SUM(Amount) OVER (ORDER BY Date) AS RunningTotal
FROM Orders;

' Excel
=IFS(G2>=1500,"Large",G2>=800,"Medium",TRUE,"Small")
=SUM($G$2:G2)

The running total uses a range that grows as you fill down: the start is locked with $, the end moves. That is what SQL's window function does in one line.

When to use which

Many analysts use both: SQL to pull a clean extract, Excel (or Power Query connected to the database) to analyse and present it.