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Philemon Adaghe
Philemon Adaghe

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Your Daily SQL Might Work โ€” But This Makes It Exceptional

If youโ€™re a Data Analyst, chances are you use ๐’๐๐‹ every single day. And if youโ€™re preparing for interviews, youโ€™ve probably realized that it's not just about writing queries it's about writing smart, efficient, and scalable ones.

  1. ๐๐ซ๐ž๐š๐ค ๐ˆ๐ญ ๐ƒ๐จ๐ฐ๐ง ๐ฐ๐ข๐ญ๐ก ๐‚๐“๐„๐ฌ (๐‚๐จ๐ฆ๐ฆ๐จ๐ง ๐“๐š๐›๐ฅ๐ž ๐„๐ฑ๐ฉ๐ซ๐ž๐ฌ๐ฌ๐ข๐จ๐ง๐ฌ)

Ever worked on a query that became an unreadable monster? CTEs let you break that down into logical steps. You can treat them like temporary views โ€” great for simplifying logic and improving collaboration across your team.

  1. ๐”๐ฌ๐ž ๐–๐ข๐ง๐๐จ๐ฐ ๐…๐ฎ๐ง๐œ๐ญ๐ข๐จ๐ง๐ฌ

Forget the mess of subqueries. With functions like ROW_NUMBER(), RANK(), LEAD() and LAG(), you can compare rows, rank items, or calculate running totals โ€” all within the same query. Total

  1. ๐’๐ฎ๐›๐ช๐ฎ๐ž๐ซ๐ข๐ž๐ฌ (๐๐ž๐ฌ๐ญ๐ž๐ ๐๐ฎ๐ž๐ซ๐ข๐ž๐ฌ)

Yes, they're old school, but nested subqueries are still powerful. Use them when you want to filter based on results of another query or isolate logic step-by-step before joining with the big picture.

  1. ๐ˆ๐ง๐๐ž๐ฑ๐ž๐ฌ & ๐๐ฎ๐ž๐ซ๐ฒ ๐Ž๐ฉ๐ญ๐ข๐ฆ๐ข๐ณ๐š๐ญ๐ข๐จ๐ง

Query taking forever? Look at your indexes. Index the columns you use in JOINs, WHERE, and GROUP BY. Even basic knowledge of how the SQL engine reads data can take your skills up a notch.

  1. ๐‰๐จ๐ข๐ง๐ฌ ๐ฏ๐ฌ. ๐’๐ฎ๐›๐ช๐ฎ๐ž๐ซ๐ข๐ž๐ฌ

Joins are usually faster and better for combining large datasets. Subqueries, on the other hand, are cleaner when doing one-off filters or smaller operations. Choose wisely based on the context.

  1. ๐‚๐€๐’๐„ ๐’๐ญ๐š๐ญ๐ž๐ฆ๐ž๐ง๐ญ๐ฌ:

Want to categorize or bucket data without creating a separate table? Use CASE. Itโ€™s ideal for conditional logic, custom labels, and grouping in a single query.

  1. ๐€๐ ๐ ๐ซ๐ž๐ ๐š๐ญ๐ข๐จ๐ง๐ฌ & ๐†๐‘๐Ž๐”๐ ๐๐˜

Most analytics questions start with "how many", "whatโ€™s the average", or "which is the highest?". SUM(), COUNT(), AVG(), etc., and pair them with GROUP BY to drive insights that matter.

  1. ๐ƒ๐š๐ญ๐ž๐ฌ ๐€๐ซ๐ž ๐€๐ฅ๐ฐ๐š๐ฒ๐ฌ ๐“๐ซ๐ข๐œ๐ค๐ฒ

Time-based analysis is everywhere: trends, cohorts, seasonality, etc. Get familiar with functions like DATEADD, DATEDIFF, DATE_TRUNC, and DATEPART to work confidently with time series data.

  1. ๐’๐ž๐ฅ๐Ÿ-๐‰๐จ๐ข๐ง๐ฌ & ๐‘๐ž๐œ๐ฎ๐ซ๐ฌ๐ข๐ฏ๐ž ๐๐ฎ๐ž๐ซ๐ข๐ž๐ฌ ๐Ÿ๐จ๐ซ ๐‡๐ข๐ž๐ซ๐š๐ซ๐œ๐ก๐ข๐ž๐ฌ

Whether it's org charts or product categories, not all data is flat. Learn how to join a table to itself or use recursive CTEs to navigate parent-child relationships effectively.

You donโ€™t need to memorize 100 functions. You need to understand 10 really well and apply them smartly. These are the concepts I keep going back to not just in interviews, but in the real world where clarity, performance, and logic matter most.

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