SQL Level 2 Certification Training – Advanced SQL Skills

Purpose of the Training: To advance learners’ skills in SQL beyond the basics by focusing on database design, complex queries, performance optimization, and real-world business scenarios. This course is designed to prepare candidates for roles in backend data handling, reporting, and data analysis.

Scope of the Course:

 Deep dive into writing optimized and complex SQL queries

 Understanding data relationships and database schema design

 Learning how to troubleshoot and optimize SQL performance

 Applying knowledge in practical business problem-solving using real datasets

 Laying the foundation for ETL processes, Power BI dashboards, and data analytics projects

Syllabus:

Module 1: Relational Database Design

 Normalization (1NF to 3NF)

 Keys: Primary, Foreign, Composite, Unique

 Entity-Relationship (ER) Diagrams

 Schema Design & Best Practices

Module 2: Advanced SQL Queries

 Subqueries (Correlated & Non-Correlated)

 Joins (INNER, LEFT, RIGHT, FULL OUTER) – Use Cases

 Set Operators (UNION, INTERSECT, EXCEPT)

 CASE WHEN Statements

Module 3: Functions and Expressions

 String Functions (LEN, CONCAT, SUBSTRING)

 Date Functions (GETDATE, DATEDIFF, FORMAT)

 Conversion Functions (CAST, CONVERT)

Module 4: Aggregations and Window Functions

 Advanced GROUP BY Techniques

 RANK, DENSE_RANK, ROW_NUMBER

 OVER() and PARTITION BY

 Common Table Expressions (CTE)

Module 5: Indexing & Optimization

 Understanding Indexes

 Query Execution Plans

 Optimization Techniques

 Avoiding SQL Pitfalls (e.g., Cartesian Products)

Eligibility:

 Completion of Certificate in SQL Essentials (Level 1) or equivalent foundational

knowledge

 SC/ST candidates aiming to build technical backend/data querying skills

 Ideal for students/graduates interested in data analyst, backend developer, or testing roles

Outcomes After Course Completion:

 Design normalized databases and optimize storage

 Write complex SQL queries to solve real-world problems

 Use SQL for reporting, data validation, and analytical solutions

 Understand performance tuning and optimization techniques

 Become job-ready for roles such as:

o Junior Data Analyst

o Database Developer

o ETL/Data Processing Executive

 Eligible to move to Power BI, Python for Data Analysis, or ETL/Automation Testing tracks

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