How to Read Other People’s SQL Queries Without Getting Lost

Opening someone else’s SQL can feel confusing fast. One look at the JOINs, aliases, and filters, and you’re lost. Here’s how to break down any query step by step and make sense of it.

Reading your own SQL is one thing. Reading someone else’s 200-line query that powers a key dashboard is something else entirely.

This article will show you how to approach other people’s SQL step by step, so you can understand what it does, spot problems, and feel confident making changes. It’s written for beginners and junior analysts who already know the basics but still feel overwhelmed by “real-world” queries.

If you’re just starting out and need a solid base, it helps a lot to go through a structured path first, like LearnSQL.com’s SQL Basics course and the SQL From A to Z track. They give you the vocabulary; this article shows you how to “read long sentences” written by others.

Why reading SQL written by others feels so hard

A long SQL query can feel worse than code in other languages, because:

• Everyone uses different formatting and naming habits.
• Some code is written by people, some by tools that generate SQL.
• The query often lives inside a report, dashboard, or ETL process you don’t fully know yet.
• You can’t see the data model in one place; you have to infer it from table and column names.

The good news: there is a repeatable way to “decode” such queries. You don’t need advanced math, just a careful, step-by-step approach.

Step 1: Start with the goal, not the syntax

Before you look at the keywords, ask one simple question: What is this query trying to answer?

You can often guess that from context:

• The name of the report or dashboard tab.
• The file name or view name (for example: daily_revenue_summary, churn_risk_scores).
• The place where the query is used (weekly marketing report, finance reconciliation, product analytics, etc.).

If you don’t know, ask a colleague or check documentation. Reading a query without knowing the question behind it is like reading the solution to a puzzle without knowing the puzzle.

Once you have a guess (“This probably calculates revenue by channel per day”), you can check later if your reading of the query matches that.

Step 2: Clean up the query so you can see its shape

Messy layout makes any query harder to understand. You don’t have to be good at manual formatting to improve this.

Work on a copy of the query (so you don’t break production code) and do one or more of these:

• Use your editor’s “Format SQL” option, if it exists.
• Paste the query into an online SQL formatter.
• Add basic line breaks yourself:

• Put each main keyword on its own line: SELECT, FROM, JOIN, WHERE, GROUP BY, HAVING, ORDER BY.
• Put each selected column on a separate line.
• Put each JOIN on a new line.

After this, you should be able to see the blocks:

• One outer SELECT
• A FROM with several JOINs
• WHERE, GROUP BY, HAVING, ORDER BY sections

That visual separation is key. Many LearnSQL.com exercises in SQL Basics and later practice courses implicitly train this eye for structure by exposing you to well-formatted queries.

Step 3: Rebuild the data model in your head

Most confusion comes from not knowing what the tables and columns mean. Spend time here; it pays off later.

3.1. Consult table and column definitions

Use any tools you have:

• Database diagrams (if your team uses them).
• System views (for example, information_schema).
• “Describe table” commands (DESCRIBE, SHOW COLUMNS, etc.).
• Internal documentation or a data catalog, if you have one.

For each key table in the query, answer:

• What does one row represent? (one customer, one order, one event, one product version, etc.)
• Which columns are identifiers (primary keys, foreign keys, business keys like email, SKU, etc.)?
• Which columns are metrics or attributes (amount, status, created_at, country, etc.)?

3.2. Draw a quick join diagram

Take a piece of paper or a whiteboard and draw:

• A box for each table (or CTE) referenced in the query.
• The table alias in brackets next to the table name (for example: customers (c)).
• Lines between boxes showing the JOIN conditions.

Then label each line with the columns used for the join, for example: c.customer_id = o.customer_id.

This diagram makes it much easier to answer:

• What is the “main” table?
• Which tables just add extra attributes?
• Where can duplicates appear?

Step 4: Read the query in a logical order

SQL is written top-to-bottom, but it doesn’t run that way in your head. A simple order that works for most queries is:

1. FROM and JOIN
2. WHERE
3. GROUP BY and HAVING
4. SELECT list (including expressions and window functions)
5. ORDER BY, LIMIT / TOP / OFFSET

For a query with subqueries:

• Start with the innermost subquery.
• Treat each subquery as “one step” in a pipeline.
• Give each step a short description in plain English.

You don’t need to rewrite the SQL yet. Just build a narrative: “First we select active customers, then we join their orders, then we aggregate by channel and day.”

This is exactly the kind of multi-step thinking you practice in LearnSQL.com’s more advanced courses like the Subqueries course.

Step 5: Pay attention to names, aliases, and comments

Cryptic aliases are a common source of confusion. In your scratch copy of the query, you are free to rename them for your own understanding.

For example, change:

FROM c AS t1
 JOIN o AS t2 ON t1.id = t2.customer_id

to something like:

FROM customers AS c
 JOIN orders AS o ON c.id = o.customer_id

Similarly, in the SELECT list:

• Try to line up expressions and their aliases.
• Rewrite unclear aliases in your notes:

• total_amount_30d instead of t_amt
• first_paid_date instead of d1

If there are comments, read them carefully. They might explain:

• Why a strange filter exists.
• Why an unusual JOIN is used.
• Why a piece of logic is kept for backward compatibility.

If there are no comments, write your own – even if it’s just for you. A simple comment like:

-- Calculate revenue per customer per month, excluding internal test accounts

will help you and future readers.

Step 6: Ask for help wisely (including ChatGPT)

Sometimes you still get stuck, even after all these steps. That’s normal.

Options:

• Ask a colleague who wrote or maintains the query.
• Ask a senior analyst or data engineer to validate your understanding.

Use tools like ChatGPT to explain parts of the query, under strict conditions:

• Do not paste confidential data, API keys, or client names.
• Remove or anonymize table and column names that reveal sensitive information.
• Paste only the structure you need help with (for example, a specific CTE, not the whole pipeline).

Ask focused questions:

• “What does this window function do?”
• “What rows will survive this join and filter?”
• “Is this GROUP BY logic consistent with the SELECT list?”

Treat AI as another helper in your toolbox, similar to a formatter or query visualizer. It should support your reasoning, not replace it.

How to practice this skill on purpose

Reading other people’s SQL is a skill you can practice, not just something that happens to you at work.

A few ideas:

• Take old queries from your team’s reporting folder and “reverse-engineer” them:
  • What was the business question?
  • Which tables are involved?
  • How would you describe the query in three lines?

In your own work:

• Leave better comments than the ones you inherited.
• Use clear aliases and meaningful names.
• Format your queries consistently.

On LearnSQL.com:

• Follow the SQL From A to Z track to see more complex but well-structured queries.
• Use Advanced SQL Practice “reading drills”: don’t just write answers; also read and explain the model solutions.

The more queries you see, the less scary the next one becomes. You’ll start recognizing patterns and saying: “Ah, this is just like that revenue report, but with an extra dimension and a slightly different filter.”

Final thoughts

You don’t have to be a senior data engineer to understand long SQL queries written by others. You just need a method.

If you want a place to practice these skills and build real confidence with SQL, explore the All Forever SQL Package from LearnSQL.com. It gives you lifetime access to every course — from SQL Basics to advanced practice sets — so you can strengthen your fundamentals, learn deeper techniques, and tackle complex queries with ease.