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Real Experience

The Hidden Job Market Where Juniors Actually Get Hired

Hey there,

Let me tell you one real story about Timothy's unorthodox job search strategy.

After months of failed applications on LinkedIn, he tried something different:

He opened Google Maps.

Searched "digital agencies near me."

Found 30 companies within driving distance.

Most people would've hit "Quick Apply" on LinkedIn and called it a day.

But Timothy discovered something interesting:

Only 20% of tech jobs are ever posted online.

The other 80%?

They exist in what I call the "shadow market."

See, in every city, there are dozens of digital agencies and small software companies.

They're constantly growing, constantly building, constantly hiring.

But they NEVER post on job boards.

Why? Because these companies operate differently.

They run on tight margins. They need talented juniors. They can't compete with Google's salaries.

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Timothy walked into these companies with his resume

Had real conversations with real people.

Showed genuine interest in their work.

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They appreciated the personal approach.

They were actively looking for juniors.

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Job offer.

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Timothy found a hidden opportunity. Got real experience. Started his tech career.

Sometimes the best opportunities aren't on job boards. Sometimes you have to look where others aren't looking.

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Here are SQL interview questions:

Basic SQL Questions

1.โ  โ What is SQL, and what is its purpose?
2.โ  โ Write a SQL query to retrieve all records from a table.
3.โ  โ How do you select specific columns from a table?
4.โ  โ What is the difference between WHERE and HAVING clauses?
5.โ  โ How do you sort data in ascending/descending order?

SQL Query Questions

1.โ  โ Write a SQL query to retrieve the top 10 records from a table based on a specific column.
2.โ  โ How do you join two tables based on a common column?
3.โ  โ Write a SQL query to retrieve data from multiple tables using subqueries.
4.โ  โ How do you use aggregate functions (SUM, AVG, MAX, MIN)?
5.โ  โ Write a SQL query to retrieve data from a table for a specific date range.

SQL Optimization Questions

1.โ  โ How do you optimize SQL query performance?
2.โ  โ What is indexing, and how does it improve query performance?
3.โ  โ How do you avoid full table scans?
4.โ  โ What is query caching, and how does it work?
5.โ  โ How do you optimize SQL queries for large datasets?

SQL Joins and Subqueries

1.โ  โ Explain the difference between INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN.
2.โ  โ Write a SQL query to retrieve data from two tables using a subquery.
3.โ  โ How do you use EXISTS and IN operators in SQL?
4.โ  โ Write a SQL query to retrieve data from multiple tables using a self-join.
5.โ  โ Explain the concept of correlated subqueries.

SQL Data Modeling

1.โ  โ Explain the concept of normalization and denormalization.
2.โ  โ How do you design a database schema for a given application?
3.โ  โ What is data redundancy, and how do you avoid it?
4.โ  โ Explain the concept of primary and foreign keys.
5.โ  โ How do you handle data inconsistencies and anomalies?

SQL Advanced Questions

1.โ  โ Explain the concept of window functions (ROW_NUMBER, RANK, etc.).
2.โ  โ Write a SQL query to retrieve data using Common Table Expressions (CTEs).
3.โ  โ How do you use dynamic SQL?
4.โ  โ Explain the concept of stored procedures and functions.
5.โ  โ Write a SQL query to retrieve data using pivot tables.

SQL Scenario-Based Questions

1.โ  โ You have two tables, Orders and Customers. Write a SQL query to retrieve all orders for customers from a specific region.
2.โ  โ You have a table with duplicate records. Write a SQL query to remove duplicates.
3.โ  โ You have a table with missing values. Write a SQL query to replace missing values with a default value.
4.โ  โ You have a table with data in an incorrect format. Write a SQL query to correct the format.
5.โ  โ You have two tables with different data types for a common column. Write a SQL query to join the tables.

SQL Behavioral Questions

1.โ  โ Can you explain a time when you optimized a slow-running SQL query?
2.โ  โ How do you handle database errors and exceptions?
3.โ  โ Can you describe a complex SQL query you wrote and why?
4.โ  โ How do you stay up-to-date with new SQL features and best practices?
5.โ  โ Can you walk me through your process for troubleshooting SQL issues?

Best Resources to learn SQL ๐Ÿ‘‡

SQL Topics for Data Analysts (https://t.me/sqlresourcestp/83)

Learn & Practice SQL (https://bit.ly/4kNb15x)

SQL Udacity Course (https://udacity.com/course/sql-for-data-analysis--ud198)

Download SQL Cheatsheet (https://t.me/sqlresourcestp/4)

Also try to apply what you learn through hands-on projects or challenges.

ENJOY LEARNING ๐Ÿ‘๐Ÿ‘

More Resources Here
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R

Like this post if you need more ๐Ÿ‘โค๏ธ

Hope it helps :)
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Learn SQL from basic to advanced level in 30 days

Week 1: SQL Basics

Day 1: Introduction to SQL and Relational Databases

Overview of SQL Syntax

Setting up a Database (MySQL, PostgreSQL, or SQL Server)


Day 2: Data Types (Numeric, String, Date, etc.)

Writing Basic SQL Queries:

SELECT, FROM

Day 3: WHERE Clause for Filtering Data

Using Logical Operators:

AND, OR, NOT

Day 4: Sorting Data: ORDER BY

Limiting Results: LIMIT and OFFSET

Understanding DISTINCT

Day 5: Aggregate Functions:

COUNT, SUM, AVG, MIN, MAX


Day 6: Grouping Data: GROUP BY and HAVING

Combining Filters with Aggregations


Day 7: Review Week 1 Topics with Hands-On Practice

Solve SQL Exercises on platforms like HackerRank, LeetCode, or W3Schools


Week 2: Intermediate SQL

Day 8: SQL JOINS:

INNER JOIN, LEFT JOIN

Day 9: SQL JOINS Continued: RIGHT JOIN, FULL OUTER JOIN, SELF JOIN

Day 10: Working with NULL Values

Using Conditional Logic with CASE Statements

Day 11: Subqueries: Simple Subqueries (Single-row and Multi-row)

Correlated Subqueries

Day 12: String Functions:

CONCAT, SUBSTRING, LENGTH, REPLACE

Day 13: Date and Time Functions: NOW, CURDATE, DATEDIFF, DATEADD

Day 14: Combining Results: UNION, UNION ALL, INTERSECT, EXCEPT

Review Week 2 Topics and Practice

Week 3: Advanced SQL

Day 15: Common Table Expressions (CTEs)

WITH Clauses and Recursive Queries

Day 16: Window Functions:

ROW_NUMBER, RANK, DENSE_RANK, NTILE

Day 17: More Window Functions:

LEAD, LAG, FIRST_VALUE, LAST_VALUE


Day 18: Creating and Managing Views

Temporary Tables and Table Variables

Day 19: Transactions and ACID Properties

Working with Indexes for Query Optimization

Day 20: Error Handling in SQL

Writing Dynamic SQL Queries


Day 21: Review Week 3 Topics with Complex Query Practice

Solve Intermediate to Advanced SQL Challenges



Week 4: Database Management and Advanced Applications

Day 22: Database Design and Normalization:

1NF, 2NF, 3NF


Day 23: Constraints in SQL:
PRIMARY KEY, FOREIGN KEY, UNIQUE, CHECK, DEFAULT


Day 24: Creating and Managing Indexes

Understanding Query Execution Plans

Day 25: Backup and Restore Strategies in SQL

Role-Based Permissions

Day 26: Pivoting and Unpivoting Data

Working with JSON and XML in SQL

Day 27: Writing Stored Procedures and Functions

Automating Processes with Triggers

Day 28: Integrating SQL with Other Tools (e.g., Python, Power BI, Tableau)

SQL in Big Data: Introduction to NoSQL

Day 29: Query Performance Tuning:

Tips and Tricks to Optimize SQL Queries


Day 30: Final Review of All Topics

Attempt SQL Projects or Case Studies (e.g., analyzing sales data, building a reporting dashboard)

Since SQL is one of the most essential skill for data analysts, I have decided to teach each topic daily in this channel for free. Like this post if you want me to continue this SQL series ๐Ÿ‘โ™ฅ๏ธ

SQL Topics for Data Analysts (https://t.me/sqlresourcestp/83)

Learn & Practice SQL (https://bit.ly/4kNb15x)

SQL interview questions: https://t.me/sqlresourcestp/94

SQL Udacity Course (https://udacity.com/course/sql-for-data-analysis--ud198)

Download SQL Cheatsheet (https://t.me/sqlresourcestp/4)

Also try to apply what you learn through hands-on projects or challenges.

ENJOY LEARNING ๐Ÿ‘๐Ÿ‘

More Resources Here
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R


Hope it helps :)
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๐‘ช๐’๐’Ž๐’‘๐’“๐’†๐’‰๐’†๐’๐’”๐’Š๐’—๐’† ๐’“๐’๐’‚๐’…๐’Ž๐’‚๐’‘ ๐’•๐’ ๐’ƒ๐’†๐’„๐’๐’Ž๐’Š๐’๐’ˆ ๐’‚ ๐’Ž๐’‚๐’”๐’•๐’†๐’“ ๐’Š๐’ ๐‘บ๐‘ธ๐‘ณ:

1. ๐‘ผ๐’๐’…๐’†๐’“๐’”๐’•๐’‚๐’๐’… ๐’•๐’‰๐’† ๐‘ฉ๐’‚๐’”๐’Š๐’„๐’” ๐’๐’‡ ๐‘บ๐‘ธ๐‘ณ

๐€. ๐ˆ๐ง๐ญ๐ซ๐จ๐๐ฎ๐œ๐ญ๐ข๐จ๐ง ๐ญ๐จ ๐ƒ๐š๐ญ๐š๐›๐š๐ฌ๐ž๐ฌ

๐–๐ก๐š๐ญ ๐ข๐ฌ ๐š ๐ƒ๐š๐ญ๐š๐›๐š๐ฌ๐ž?: Understanding the concept of databases and relational databases.

๐ƒ๐š๐ญ๐š๐›๐š๐ฌ๐ž ๐Œ๐š๐ง๐š๐ ๐ž๐ฆ๐ž๐ง๐ญ ๐’๐ฒ๐ฌ๐ญ๐ž๐ฆ๐ฌ (๐ƒ๐๐Œ๐’): Learn about different DBMS like MySQL, PostgreSQL, SQL Server, Oracle.

๐. ๐๐š๐ฌ๐ข๐œ ๐’๐๐‹ ๐‚๐จ๐ฆ๐ฆ๐š๐ง๐๐ฌ

๐ƒ๐š๐ญ๐š ๐‘๐ž๐ญ๐ซ๐ข๐ž๐ฏ๐š๐ฅ:
๐’๐„๐‹๐„๐‚๐“: Basic retrieval of data.
๐–๐‡๐„๐‘๐„: Filtering data based on conditions.
๐Ž๐‘๐ƒ๐„๐‘ ๐๐˜: Sorting results.
๐‹๐ˆ๐Œ๐ˆ๐“: Limiting the number of rows returned.

๐ƒ๐š๐ญ๐š ๐Œ๐š๐ง๐ข๐ฉ๐ฎ๐ฅ๐š๐ญ๐ข๐จ๐ง:
๐ˆ๐๐’๐„๐‘๐“: Adding new data.
๐”๐๐ƒ๐€๐“๐„: Modifying existing data.
๐ƒ๐„๐‹๐„๐“๐„: Removing data.

2. ๐ˆ๐ง๐ญ๐ž๐ซ๐ฆ๐ž๐๐ข๐š๐ญ๐ž ๐’๐๐‹ ๐’๐ค๐ข๐ฅ๐ฅ๐ฌ
๐€. ๐€๐๐ฏ๐š๐ง๐œ๐ž๐ ๐ƒ๐š๐ญ๐š ๐‘๐ž๐ญ๐ซ๐ข๐ž๐ฏ๐š๐ฅ

๐‰๐Ž๐ˆ๐๐ฌ: Understanding different types of joins (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN).
๐€๐ ๐ ๐ซ๐ž๐ ๐š๐ญ๐ž ๐…๐ฎ๐ง๐œ๐ญ๐ข๐จ๐ง๐ฌ: Using functions like COUNT, SUM, AVG, MIN, MAX.
๐†๐‘๐Ž๐”๐ ๐๐˜: Grouping data to perform aggregate calculations.
๐‡๐€๐•๐ˆ๐๐†: Filtering groups based on aggregate values.

๐. ๐’๐ฎ๐›๐ช๐ฎ๐ž๐ซ๐ข๐ž๐ฌ ๐š๐ง๐ ๐๐ž๐ฌ๐ญ๐ž๐ ๐๐ฎ๐ž๐ซ๐ข๐ž๐ฌ
๐’๐ฎ๐›๐ช๐ฎ๐ž๐ซ๐ข๐ž๐ฌ: Using queries within queries.
๐‚๐จ๐ซ๐ซ๐ž๐ฅ๐š๐ญ๐ž๐ ๐’๐ฎ๐›๐ช๐ฎ๐ž๐ซ๐ข๐ž๐ฌ: Subqueries that reference columns from the outer query.

๐‘ช. ๐‘ซ๐’‚๐’•๐’‚ ๐‘ซ๐’†๐’‡๐’Š๐’๐’Š๐’•๐’Š๐’๐’ ๐‘ณ๐’‚๐’๐’ˆ๐’–๐’‚๐’ˆ๐’† (๐‘ซ๐‘ซ๐‘ณ)
๐‚๐ซ๐ž๐š๐ญ๐ข๐ง๐  ๐“๐š๐›๐ฅ๐ž๐ฌ: CREATE TABLE.
๐Œ๐จ๐๐ข๐Ÿ๐ฒ๐ข๐ง๐  ๐“๐š๐›๐ฅ๐ž๐ฌ: ALTER TABLE.
๐‘น๐’†๐’Ž๐’๐’—๐’Š๐’๐’ˆ ๐‘ป๐’‚๐’ƒ๐’๐’†๐’”: DROP TABLE.

3. ๐€๐๐ฏ๐š๐ง๐œ๐ž๐ ๐’๐๐‹ ๐“๐ž๐œ๐ก๐ง๐ข๐ช๐ฎ๐ž๐ฌ
๐€. ๐๐ž๐ซ๐Ÿ๐จ๐ซ๐ฆ๐š๐ง๐œ๐ž ๐Ž๐ฉ๐ญ๐ข๐ฆ๐ข๐ณ๐š๐ญ๐ข๐จ๐ง
๐ˆ๐ง๐๐ž๐ฑ๐ž๐ฌ: Understanding and creating indexes to speed up queries.
๐๐ฎ๐ž๐ซ๐ฒ ๐Ž๐ฉ๐ญ๐ข๐ฆ๐ข๐ณ๐š๐ญ๐ข๐จ๐ง: Techniques to write efficient SQL queries.

๐. ๐€๐๐ฏ๐š๐ง๐œ๐ž๐ ๐’๐๐‹ ๐…๐ฎ๐ง๐œ๐ญ๐ข๐จ๐ง๐ฌ
๐–๐ข๐ง๐๐จ๐ฐ ๐…๐ฎ๐ง๐œ๐ญ๐ข๐จ๐ง๐ฌ: Using functions like ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG.
๐‚๐“๐„ (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): Using WITH to create temporary result sets.

๐‚. ๐“๐ซ๐š๐ง๐ฌ๐š๐œ๐ญ๐ข๐จ๐ง๐ฌ ๐š๐ง๐ ๐‚๐จ๐ง๐œ๐ฎ๐ซ๐ซ๐ž๐ง๐œ๐ฒ
๐“๐ซ๐š๐ง๐ฌ๐š๐œ๐ญ๐ข๐จ๐ง๐ฌ: Using BEGIN, COMMIT, ROLLBACK.
๐‚๐จ๐ง๐œ๐ฎ๐ซ๐ซ๐ž๐ง๐œ๐ฒ ๐‚๐จ๐ง๐ญ๐ซ๐จ๐ฅ: Understanding isolation levels and locking mechanisms.

4. ๐๐ซ๐š๐œ๐ญ๐ข๐œ๐š๐ฅ ๐€๐ฉ๐ฉ๐ฅ๐ข๐œ๐š๐ญ๐ข๐จ๐ง๐ฌ ๐š๐ง๐ ๐‘๐ž๐š๐ฅ-๐–๐จ๐ซ๐ฅ๐ ๐’๐œ๐ž๐ง๐š๐ซ๐ข๐จ๐ฌ
๐€. ๐ƒ๐š๐ญ๐š๐›๐š๐ฌ๐ž ๐ƒ๐ž๐ฌ๐ข๐ ๐ง
๐๐จ๐ซ๐ฆ๐š๐ฅ๐ข๐ณ๐š๐ญ๐ข๐จ๐ง: Understanding normal forms and how to normalize databases.
๐„๐‘ ๐ƒ๐ข๐š๐ ๐ซ๐š๐ฆ๐ฌ: Creating Entity-Relationship diagrams to model databases.

๐. ๐ƒ๐š๐ญ๐š ๐ˆ๐ง๐ญ๐ž๐ ๐ซ๐š๐ญ๐ข๐จ๐ง
๐„๐“๐‹ ๐๐ซ๐จ๐œ๐ž๐ฌ๐ฌ๐ž๐ฌ: Extract, Transform, Load processes for data integration.

๐’๐ญ๐จ๐ซ๐ž๐ ๐๐ซ๐จ๐œ๐ž๐๐ฎ๐ซ๐ž๐ฌ ๐š๐ง๐ ๐“๐ซ๐ข๐ ๐ ๐ž๐ซ๐ฌ: Writing and using stored procedures and triggers for complex logic and automation.

๐‚. ๐‚๐š๐ฌ๐ž ๐’๐ญ๐ฎ๐๐ข๐ž๐ฌ ๐š๐ง๐ ๐๐ซ๐จ๐ฃ๐ž๐œ๐ญ๐ฌ
๐‘๐ž๐š๐ฅ-๐–๐จ๐ซ๐ฅ๐ ๐’๐œ๐ž๐ง๐š๐ซ๐ข๐จ๐ฌ: Work on case studies involving complex database operations.

๐‚๐š๐ฉ๐ฌ๐ญ๐จ๐ง๐ž ๐๐ซ๐จ๐ฃ๐ž๐œ๐ญ๐ฌ: Develop comprehensive projects that showcase your SQL expertise.

๐‘๐ž๐ฌ๐จ๐ฎ๐ซ๐œ๐ž๐ฌ ๐š๐ง๐ ๐“๐จ๐จ๐ฅ๐ฌ
๐๐จ๐จ๐ค๐ฌ: "SQL in 10 Minutes, Sams Teach Yourself" by Ben Forta, "SQL for Data Scientists" by Renee M. P. Teate.
๐Ž๐ง๐ฅ๐ข๐ง๐ž ๐๐ฅ๐š๐ญ๐Ÿ๐จ๐ซ๐ฆ๐ฌ: Coursera, Udacity, edX, Khan Academy.
๐๐ซ๐š๐œ๐ญ๐ข๐œ๐ž ๐๐ฅ๐š๐ญ๐Ÿ๐จ๐ซ๐ฆ๐ฌ: LeetCode, HackerRank, Mode Analytics, SQLZoo.
๐—š๐—ผ๐—ผ๐—ด๐—น๐—ฒ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€๐Ÿš€๐Ÿ’ป 

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๐Ÿ”ฐ SQL Roadmap for Beginners 2025
โ”œโ”€โ”€ ๐Ÿ—ƒ Introduction to Databases & SQL
โ”œโ”€โ”€ ๐Ÿ“„ SQL vs NoSQL (Just Basics)
โ”œโ”€โ”€ ๐Ÿงฑ Database Concepts (Tables, Rows, Columns, Keys)
โ”œโ”€โ”€ ๐Ÿ” Basic SQL Queries (SELECT, WHERE)
โ”œโ”€โ”€ โœ๏ธ Filtering & Sorting Data (ORDER BY, LIMIT)
โ”œโ”€โ”€ ๐Ÿ”ข SQL Operators (IN, BETWEEN, LIKE, AND, OR)
โ”œโ”€โ”€ ๐Ÿ“Š Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)
โ”œโ”€โ”€ ๐Ÿ‘ฅ GROUP BY & HAVING Clauses
โ”œโ”€โ”€ ๐Ÿ”— SQL JOINS (INNER, LEFT, RIGHT, FULL, SELF)
โ”œโ”€โ”€ ๐Ÿ“ฆ Subqueries & Nested Queries
โ”œโ”€โ”€ ๐Ÿท Aliases & Case Statements
โ”œโ”€โ”€ ๐Ÿงพ Views & Indexes (Basics)
โ”œโ”€โ”€ ๐Ÿง  Common Table Expressions (CTEs)
โ”œโ”€โ”€ ๐Ÿ”„ Window Functions (ROW_NUMBER, RANK, PARTITION BY)
โ”œโ”€โ”€ โš™๏ธ Data Manipulation (INSERT, UPDATE, DELETE)
โ”œโ”€โ”€ ๐Ÿงฑ Data Definition (CREATE, ALTER, DROP)
โ”œโ”€โ”€ ๐Ÿ” Constraints & Relationships (PK, FK, UNIQUE, CHECK)
โ”œโ”€โ”€ ๐Ÿงช Real-world SQL Scenarios & Challenges

Like for detailed explanation โค๏ธ

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SQL Essentials for Data Analysts
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SQL is one of the core languages used in data science, powering everything from quick data retrieval to complex deep dive analysis. Whether you're a seasoned data scientist or just starting out, mastering SQL can boost your ability to analyze data, create robust pipelines, and deliver actionable insights.

Letโ€™s dive into a comprehensive guide on SQL for Data Science!

I have broken it down into three key sections to help you:

๐Ÿญ. ๐—ฆ๐—ค๐—Ÿ ๐—–๐—ผ๐—ป๐—ฐ๐—ฒ๐—ฝ๐˜๐˜€:
Get a handle on the essentials -> SELECT statements, filtering, aggregations, joins, window functions, and more.

๐Ÿฎ. ๐—ฆ๐—ค๐—Ÿ ๐—ถ๐—ป ๐——๐—ฎ๐˜†-๐˜๐—ผ-๐——๐—ฎ๐˜† ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ:
See how SQL fits into the daily data science workflow. From quick data queries and deep-dive analysis to building pipelines and dashboards, SQL is really useful for data scientists, especially for product data scientists.

๐Ÿฏ. ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ฆ๐—ค๐—Ÿ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„๐˜€:
Learn what interviewers look for in terms of technical skills, design and engineering expertise, communication abilities, and the importance of speed and accuracy.

SQL Resources: https://t.me/sqlresourcestp
โค1
SQL Joins โœ