docs(sql): add dedicated folder for HAVING clause with detailed explanation

What
- Created `HAVING Clauses In SQL` folder to document the role and usage of the `HAVING` clause.
- Explained how `HAVING` is used to filter aggregated/grouped data after applying `GROUP BY`.
- Highlighted difference between `WHERE` (row-level filtering) and `HAVING` (group-level filtering).
- Provided syntax, rules, and examples for clarity.

Why
- Many developers confuse `WHERE` and `HAVING` when writing aggregate queries.
- Proper documentation helps reinforce that `HAVING` operates on grouped results, not individual rows.
- Essential for analytics, reporting, and dashboards that require grouped filtering.

How
- Structured the content into:
  - Definition and purpose of `HAVING`.
  - Syntax examples:
    `SELECT dept, COUNT(*) FROM employees GROUP BY dept HAVING COUNT(*) > 5;`
  - Explanation of how it follows `GROUP BY` in query order.
  - Edge cases and common mistakes (e.g., using `HAVING` without aggregation).
- Connected examples with real-life business use cases.

Key notes
- `HAVING` must be used with `GROUP BY` when filtering aggregated results.
- You can use aggregate functions directly in `HAVING` conditions.
- Without `GROUP BY`, `HAVING` can still filter on aggregate over the entire table.

Real-life applications
- HR: list departments with more than 10 employees.
- Sales: find products whose total sales exceed $1000.
- Education: show courses with an average score below a threshold.
- Finance: display accounts with total transactions over a set limit.

Future improvements
- Add combined examples with `WHERE` + `GROUP BY` + `HAVING`.
- Cover performance considerations when using `HAVING` on large datasets.
- Include advanced SQL dialect support (MySQL, PostgreSQL, Oracle, SQL Server differences).

Signed-off-by: https://github.com/Someshdiwan <[email protected]>

Author: Someshdiwan