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Practice

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deck​

1. Beyond Basics: Where to Go Next​

Now that you’ve mastered the core SQL toolkit, the next step is learning advanced techniques that scale with real-world data.

Advanced SQL allows you to:

  • Compare rows and track rankings or running totals
  • Reuse logic cleanly across multiple queries
  • Optimize performance for large, production-level datasets

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2. Key Advanced Concepts​

ConceptWhat It Enables
Window FunctionsRow comparisons, rankings, running totals
Common Table Expr.Cleaner, modular logic in complex queries
ViewsSave and reuse reusable query logic
IndexesSpeed up queries by optimizing how data is read
EXPLAIN PlansDiagnose and improve slow queries

SQL isn’t just a query language — it’s the connective tissue of modern data systems.


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3. Tools You'll Encounter​

As you move forward, SQL will appear everywhere:

  • BI tools: Looker, Power BI, Tableau
  • Data platforms: BigQuery, Snowflake, Redshift
  • Pipelines: dbt, Airflow, ETL scripts
  • APIs & Backends: embedded SQL logic in real apps

Learning SQL isn't just theory—it connects across the stack.


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4. Practice Ideas to Level Up​

Ways to apply your SQL skills:

  • Analyze public datasets (e.g. NYC Taxi, COVID stats)
  • Build a small dashboard tracking real metrics you care about
  • Share your work — start a GitHub repo of SQL mini-projects
  • Join a data challenge on Kaggle or SQLPad.io

Every real dataset you touch strengthens your problem-solving intuition.


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5. Keep Going: Learn by Doing​

Don’t stop here — keep experimenting and refining:

  • Revisit and optimize queries you’ve already written
  • Rewrite them using CTEs, RANK(), or window functions
  • Explore new questions hidden in familiar datasets

SQL mastery doesn’t come from memorization — it comes from solving real problems with clarity and intent.

You’re ready for that next challenge!

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