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deck
1. Core Topics We Covered
This course emphasized practical SQL for real-world tasks. Here’s a quick look at the key topics you’ve mastered:
| Category | SQL Features Used |
|---|---|
| Filtering | WHERE, AND, OR, IN, BETWEEN |
| Sorting & Limits | ORDER BY, LIMIT |
| Aggregation | COUNT, SUM, AVG, ROUND |
| Grouping | GROUP BY, HAVING |
| Joins | INNER JOIN, LEFT JOIN |
| Subqueries | In WHERE, HAVING, and SELECT clauses |
| Logic & Control | CASE, IS NULL, date grouping (STRFTIME) |
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2. Where Each Concept Shined
| Concept | Real-Life Use Case Example |
|---|---|
JOIN | Merging orders with customer data |
GROUP BY | Summarizing product categories or appointment counts |
LEFT JOIN | Finding clients who never purchased |
HAVING | Filtering groups (e.g. customers who spent > $400) |
CASE | Splitting data into segments (e.g. urgent vs routine) |
| Subquery | Comparing with average metrics (e.g. price, sales) |
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3. Debugging Patterns You Faced
As queries got more complex, you learned to catch issues like:
- Incorrect joins (e.g. wrong key or join type)
- Missing
GROUP BYwith aggregates - Filters applied in the wrong stage (
WHEREvsHAVING) - Syntax that worked but returned the wrong results
Debugging isn't just fixing — it's about aligning logic with purpose.
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4. Application Contexts
You've touched datasets from:
- Online retail → product, stock, orders
- Delivery logistics → drivers, regional trends
- Event ticketing → purchases, high spenders
- Hospital systems → visits, time-based metrics
Each domain showed how data structure shapes query design.
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5. Building Analyst Mindset
Think beyond queries—ask:
- What insight does this result offer?
- Could this scale with more data?
- Is the logic understandable to someone else on my team?
You're not just writing code—you're writing analysis.
That’s what true SQL mastery looks like.
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