SQL's Hidden Travel Itinerary: One Join Could Derail Everything

“SQL doesn’t break when you write it wrong. It breaks when you misunderstand how it works.”

I learned that the hard way.

I once used an INNER JOIN when I should’ve used a LEFT JOIN. For two weeks, none of our new leads were showing up in our Salesforce dashboard. The numbers made it look like our pipeline was $5 million under target, when we were actually $2 million over.

Leadership started pressing Marketing.

• “Where are the leads?”

• “Why is the funnel dry?”

• “Should we reallocate budget?”

They even threatened to pull funding from campaigns that were actually working. All of it… triggered by one bad line of SQL.

That moment changed how I teach SQL, and how I think about what really matters in data work. Today, I want to break down the 3 concepts every data professional needs to master to avoid these kinds of disasters.

SQL Execution Order: The Travel Itinerary

Most people write SQL like it’s a to-do list.
Start with SELECT, then FROM, then maybe WHERE.

But that’s not how SQL works under the hood.

Here’s the real execution order:

1. FROM — What table(s) are we starting from?

2. WHERE — Filter individual rows

3. GROUP BY — Aggregate into logical groupings

4. HAVING — Filter those aggregated groups

5. SELECT — Choose what fields to return

6. ORDER BY — Sort the final result

Think of it like a flight: You don’t assign seats (SELECT) before people pass security (WHERE) or reach their gate (GROUP BY).

Why This Matters

If you debug based on the written order, you’re looking in the wrong place.
JOIN logic happens during the FROM clause, so if you mess up your JOINs, you’ve broken the foundation before the query even gets to filtering or selecting.

JOINs: Party Invites and Pie (And Pandemonium)

Let’s say you’re planning a potluck.

• List A: Who’s invited

• List B: What they’re bringing

Here’s how JOIN types translate:

• INNER JOIN: Only guests who are invited and bring something

• LEFT JOIN: Everyone invited, even if they bring nothing

• CARTESIAN JOIN: Every person with every item. Chaos.

💥 Real Story: One JOIN, $7M in Fallout

I once used the wrong JOIN type in a production dashboard… an INNER instead of a LEFT.
For half the month, none of our new leads appeared.
Our revenue funnel looked like it was falling off a cliff.
Leadership began demanding answers. Marketing was told their budget might be pulled.

We were actually overperforming. But one clause distorted everything.

This is how dashboards lie. This is how trust dies.

🧠 Can You Spot the Problem?

What’s wrong with this query?

SELECT c.customer_id, 
l.lead_id
FROM customers c
   INNER JOIN leads l ON c.customer_id = l.customer_id
WHERE l.created_date >= '2024-01-01';

Hint: What happens to customers who don’t have lead records yet?

Quick self-check: What’s your default JOIN? Why?

Window Functions: The Range Game

If you’ve watched The Price Is Right, you might remember the Range Game…you slide a window along a price board and hope the actual price falls inside.

Think of the “price range” as the window frame of data rows we’re calculating over.

That’s how window functions work. They let you look at a row in context…not just individually or in groups.

👇 Example:

SELECT
  date,
  sales,
  AVG(sales) OVER (
    ORDER BY date
    ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING
  ) AS five_day_avg
FROM daily_sales;

This creates a 5-day rolling average. Every row gets calculated based on its neighbors…not just its own value.

GROUP BY vs. Window Functions

• GROUP BY collapses rows: one row per group

• Window functions annotate rows: you keep all rows and add context

Think: grouping vs. enriching.

Bonus Word: SQL Itself

SQL gets a bad rap.

It’s old.
It’s clunky.
It’s not as “cool” as Python or Rust or ChatGPT prompts.

But SQL still runs every serious data system in the world…and for good reason.

🛠 SQL Sub-Languages:

• DDL – Data Definition: CREATE, ALTER, DROP

• DML – Data Manipulation: INSERT, UPDATE, DELETE

• DCL – Data Control: GRANT, REVOKE

• TCL – Transaction Control: COMMIT, ROLLBACK

If you're only using SELECT *, you're leaving 90% of SQL's power untapped.

📥 Next Step: Upgrade Your SQL

🎓 Watch Lesson 3: SQL Fundamentals in my Data Engineering 101 series
📥 Download the SQL Cheat Sheet (PDF)
🔁 Share this post with a teammate who defaults to SELECT * and hopes for the best.

💬 Your Turn!

• What’s your most painful SQL mistake?

• What JOIN do you default to, and why?

• When’s the last time SQL surprised you?

Let me know in the comments…or tag me on LinkedIn.