Stage 1: Beginner

Objective: Understand the basics of SQL and its use in querying databases.

Topics to Learn:

1. Introduction to Databases
   • What is a database?
   • Types of databases (Relational vs. NoSQL).
2. SQL Basics
   • SQL syntax.
   • Data types (integer, text, date, etc.).
3. Basic Queries
   • SELECT, FROM, WHERE.
   • Simple conditions using AND, OR, NOT.
4. Sorting and Filtering
   • ORDER BY, LIMIT, OFFSET.

Practice:

• Query a sample database like SQLite or a free dataset (e.g., public CSV files uploaded into a database).

Resources:

• Books: SQL in 10 Minutes, Sams Teach Yourself by Ben Forta.
• Online Courses: SQL modules on Khan Academy, freeCodeCamp, or Codecademy.

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Stage 2: Intermediate

Objective: Work with more complex queries and database structures.

Topics to Learn:

1. Joins
   • Inner Join, Left Join, Right Join, Full Outer Join.
2. Aggregations and Grouping
   • GROUP BY, HAVING, COUNT, SUM, AVG, MIN, MAX.
3. Subqueries
   • Using subqueries in SELECT, FROM, and WHERE clauses.
4. Data Manipulation
   • INSERT, UPDATE, DELETE.

Practice:

• Build queries for real-world scenarios, like sales data analysis.
• Create a small database schema and populate it with sample data.

Resources:

• Tools: Install and use MySQL, PostgreSQL, or SQLite.
• Courses: The Complete SQL Bootcamp by Udemy.

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Stage 3: Advanced

Objective: Master database optimization and advanced SQL techniques.

Topics to Learn:

1. Database Design
   • Normalization and denormalization.
   • Primary and foreign keys, constraints.
2. Advanced Joins
   • Self joins, cross joins.
3. Window Functions
   • ROW_NUMBER(), RANK(), NTILE(), LAG(), LEAD().
4. Indexes
   • Creating and using indexes for query optimization.
5. Transactions
   • Understanding BEGIN, COMMIT, ROLLBACK.
   • ACID properties.

Practice:

• Design and implement a relational database schema for a medium-sized project, such as an inventory system.
• Optimize complex queries.

Resources:

• Books: SQL Performance Explained by Markus Winand.
• Courses: Advanced SQL for Data Scientists on Coursera.

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Stage 4: Expert

Objective: Specialize in database administration and advanced problem-solving.

Topics to Learn:

1. Stored Procedures and Functions
   • Creating and using stored procedures and functions.
2. Database Administration
   • Backups, restores, user permissions.
   • Monitoring and performance tuning.
3. Data Warehousing
   • Star schema, snowflake schema.
4. NoSQL Integration
   • Hybrid systems combining SQL and NoSQL.
5. Big Data with SQL
   • SQL in tools like Hive, BigQuery, and Snowflake.

Practice:

• Work on projects that require large-scale database handling, such as a recommendation system or a log analysis platform.
• Participate in SQL coding challenges on platforms like LeetCode or HackerRank.

Resources:

• Books: SQL Antipatterns by Bill Karwin.
• Courses: Data Engineering on Google Cloud (covers BigQuery).

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Stage 5: Mastery

Objective: Build a deep understanding of database systems and architecture.

Topics to Learn:

1. Database Internals
   • How SQL engines work.
   • Query execution plans and optimization.
2. Distributed Databases
   • Sharding, replication, and clustering.
   • Working with distributed SQL systems like CockroachDB.
3. Real-time Databases
   • Integration with tools like Apache Kafka or Redis.

Practice:

• Build a custom database application.
• Contribute to open-source SQL or database-related projects.

Resources:

• Books: Designing Data-Intensive Applications by Martin Kleppmann.
• Communities: Join SQL communities on LinkedIn, Reddit, or Stack Overflow.

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Tips for Progression:

• Practice daily, even if it’s just 20 minutes.
• Work on real-world projects to solidify your understanding.
• Continuously explore new SQL-based technologies and frameworks.