Day 91 of Learning MERN Stack

Hello Dev Community! 👋

It is officially Day 91 of my 100-day full-stack engineering streak! 🎯 Yesterday, I reached the 90% milestone by cracking compound matching queries. Today, I broke into heavy-duty data transformation and string analytics on HackerRank by mastering: SQL Exclusion Operators (NOT REGEXP), CONCAT() dynamic formatting, and advanced GROUP BY structural analytics! 📊🔥

In enterprise backend applications, data reporting requires clean formatting—like appending metadata tags next to usernames or generating automated system summaries directly from your database tier.

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🧠 Breaking Down the Day 91 Engineering Challenges

As tracked inside my workspace scripts across "Screenshot (198).png", "Screenshot (199).png", and "Screenshot (200).png", I built full local environments to stress-test these query structures:

1. Advanced Pattern Exclusions (Station Series)

• The Goal: Isolate record fields that do not conform to vowel arrays at their boundary lines.
• The Execution: Used the NOT REGEXP operator combined with caret (^) and dollar ($) anchors to seamlessly block matched arrays:

sql
-- Filtering out starting vowel strings
SELECT CITY FROM STATION WHERE CITY NOT REGEXP "^(a|e|i|o|u)";

-- Filtering out ending vowel strings
SELECT DISTINCT CITY FROM STATION WHERE CITY NOT REGEXP "(a|e|i|o|u)$"; -- Query 1: Dynamic Formatting with String Sub-Slicing
SELECT CONCAT(Name, "(", substring(OCCUPATION, 1, 1), ")")
FROM OCCUPATIONS
ORDER BY NAME;

-- Query 2: Analytical Aggregation Summary
SELECT CONCAT('There are a total of ', COUNT(occupation), ' ', LOWER(occupation), 's.')
FROM OCCUPATIONS
GROUP BY occupation
ORDER BY COUNT(occupation) ASC, occupation ASC;