| Chapter | Title | Description |
|---|---|---|
| Ch 01 | Basic Concepts | Getting started with SQL, understanding the Relational Model, and working with Tables, Queries, and Result Sets. |
| Ch 02 | Data Types | Learn about Metadata, ACID properties (Atomicity, Consistency, Isolation, Durability), and their importance in databases. |
| Ch 03 | Putting Data In | Master the INSERT statement anatomy and understand type conversions. |
| Ch 04 | Default Values | Work with Primary Keys, GUID, Auto-Increment, and copy data between tables. |
| Chapter | Title | Description |
|---|---|---|
| Ch 05 | Basic Queries | Understand the anatomy of SELECT statements and apply filters to retrieve specific data. |
| Ch 06 | General Equality and Ordering | Use expressions and SQL-specific predicates for advanced filtering and sorting. |
| Ch 07 | Expressions | Master Arithmetic, Bitwise, and String operators for data manipulation. |
| Ch 08 | Transient Tables | Work with NULL values, tri-state logic, and ANSI join syntax. |
| Chapter | Title | Description |
|---|---|---|
| Ch 09 | The USING Clause | Use EXISTS predicate, LEFT JOIN/IS NULL, NOT IN, tri-state logic, and NOT EXISTS for complex queries. |
| Ch 10 | Advanced Queries | Perform Aggregation, Grouping, Ordering, use DISTINCT, UNION, and INTERSECT. |
| Ch 11 | Queries within Queries | Master Nested Queries, Common Table Expressions (CTEs), Window Functions, Recursive Queries, Array Functions, and JSON data handling. |
| Chapter | Title | Description |
|---|---|---|
| Ch 12 | Data Organization | Understand Entity-Relationship Models, Constraints, Relationships, and Normalization techniques. |
| Ch 13 | Performance | Learn about B-Tree indexing strategies, statistics, histograms, and keeping data in order for optimal performance. |
| Ch 14 | Join Algorithms | Explore Nested Loops, Merge Join, and Hash Join algorithms for efficient data retrieval. |
| Chapter | Title | Description |
|---|---|---|
| Ch 15 | Server-Side Programming | Work with Sessions, Transactions, Atomicity, Write Concurrency, and Read Concurrency. |
| Ch 16 | Cursors, Stored Procedures & Triggers | Master Cursors, Stored Procedures, Triggers, and Materialized Views. |
| Chapter | Title | Description |
|---|---|---|
| Ch 17 | Client-Side Programming | Understand Database Clients, Parameterized Queries, and Prepared Statements. |
| Ch 18 | Plan Caching | Learn about Object-Relational Mappers (ORM), Code-First Approach, and Migrations. |
| Ch 19 | Design and Management | Explore Use Patterns, Data Warehousing, and ETL (Extract, Transform, Load) processes. |
| Ch 20 | In the Cloud | Understand Clustering, Database Splitting, and Sharding for cloud-based databases. |
| Skill Area | Key Takeaways |
|---|---|
| 🗄️ Database Fundamentals | Understand relational models, ACID properties, and data types |
| 📝 Query Writing | Write efficient SELECT, INSERT, UPDATE, DELETE queries |
| 🔗 Joins & Relationships | Master INNER, LEFT, RIGHT, FULL joins and relationships |
| 📊 Data Aggregation | Use GROUP BY, HAVING, and aggregate functions |
| 🧠 Subqueries & CTEs | Write nested queries and Common Table Expressions |
| 🚀 Performance Tuning | Optimize queries using indexing and join algorithms |
| 🛠️ Stored Procedures | Build reusable database logic with procedures and triggers |
| ☁️ Cloud Databases | Understand clustering, sharding, and distributed databases |
| 📈 Data Warehousing | Work with ETL processes and data warehouse design |
| Tool / Technology | Purpose |
|---|---|
| MySQL | Open-source relational database |
| PostgreSQL | Advanced open-source database |
| Microsoft SQL Server | Enterprise database solution |
| Oracle Database | Large-scale enterprise database |
| SQLite | Lightweight embedded database |
| MongoDB | NoSQL database (JSON data handling) |
| Azure SQL / AWS RDS | Cloud-based databases |
| Module | Chapters | Focus Area |
|---|---|---|
| Module 1 | Ch 01 – 04 | Introduction, Data Types, INSERT, Default Values |
| Module 2 | Ch 05 – 08 | SELECT, Filters, Expressions, Joins |
| Module 3 | Ch 09 – 11 | Advanced Joins, Subqueries, CTEs, Window Functions |
| Module 4 | Ch 12 – 14 | Data Organization, Normalization, Performance, Join Algorithms |
| Module 5 | Ch 15 – 16 | Transactions, Stored Procedures, Triggers |
| Module 6 | Ch 17 – 20 | Client-Side, ORM, ETL, Cloud Databases |
| Job Role | Average Salary (India) |
|---|---|
| SQL Developer | ₹4–10 LPA |
| Database Administrator (DBA) | ₹5–15 LPA |
| Data Analyst | ₹5–12 LPA |
| Business Intelligence Analyst | ₹6–14 LPA |
| Data Engineer | ₹8–20 LPA |
| Backend Developer | ₹6–16 LPA |
| Cloud Database Engineer | ₹10–25 LPA |
Beginners – No prior database knowledge required
Data Analysts – Want to query databases for insights
Developers – Need to integrate databases with applications
Students & Freshers – Build a strong foundation in databases
IT Professionals – Looking to specialize in database management
Career Switchers – Transition into data-driven roles
| Query | Concept Covered |
|---|---|
| SELECT * FROM employees | Basic SELECT |
| WHERE salary > 50000 | Filters |
| JOIN departments ON employees.dept_id = departments.id | Joins |
| GROUP BY department_id | Aggregation |
| WITH CTE AS (…) | Common Table Expressions |
| ROW_NUMBER() OVER (PARTITION BY dept) | Window Functions |
| CREATE PROCEDURE get_employees | Stored Procedures |
| CREATE INDEX idx_salary | Indexing |
| Certification | Provider |
|---|---|
| Oracle Certified Professional (OCP) | Oracle |
| Microsoft Certified: Azure Database Administrator | Microsoft |
| MySQL Database Administrator | Oracle |
| PostgreSQL Certification | EDB |
| IBM Data Science Professional Certificate | IBM |
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