Technology & IT

Learn from : ANAND DWIVEDI
Python Programing, java, Data science, Data Structure, Computer Networking, Web & mobile technologies, C++, C++ Concepts
Course Language: English
Course Fee
$109.00

Course Fee
$109.00
Instructor Bio:
I am an Assistant Professor in Computer Science with a focus on computer programming and software development. I teach core programming languages such as C, C++, Python, and Java, and guide students in developing logical thinking and coding skills. My interests include algorithms, web development, databases, and emerging technologies. I aim to create a hands-on learning environment using tools like Visual Studio Code and GitHub. With a passion for teaching and mentoring, I support student innovation through projects and research. I believe in blending theoretical knowledge with practical application to prepare students for real-world challenges in technology
VIEW FULL PROFILE56 Weeks
20
DAILY
Course Description:
This Advanced SQL course enhances your skills in complex queries, joins, subqueries, CTEs, window functions, and performance tuning. It covers transaction control, indexing, views, procedures, and real-world database scenarios. Ideal for aspiring data professionals, it empowers you to manage, analyze, and optimize large-scale relational databases effectively.
Advanced SQL for Data Engineering – Syllabus (6 Points)
Advanced Query Techniques
Subqueries, nested queries, common table expressions (CTEs), and set operations (UNION, INTERSECT, EXCEPT).
Joins and Data Relationships
Inner, outer, cross, and self joins; multi-table queries and relational data modeling.
Window and Aggregate Functions
Use of RANK(), ROW_NUMBER(), LEAD(), LAG(), PARTITION BY, and complex groupings.
Performance Tuning and Indexing
Query optimization, execution plans, indexes, and best practices for efficient data access.
ETL and Data Transformation
SQL for Extract, Transform, Load (ETL) processes, data cleaning, and pipeline integration.
Procedures, Transactions, and Security
Stored procedures, triggers, transactions (ACID), error handling, and user/data access control.
Course Curriculum:
Advanced SQL for Data Engineering – Syllabus (6 Points)
Advanced Query Techniques
Subqueries, nested queries, common table expressions (CTEs), and set operations (UNION, INTERSECT, EXCEPT).
Joins and Data Relationships
Inner, outer, cross, and self joins; multi-table queries and relational data modeling.
Window and Aggregate Functions
Use of RANK(), ROW_NUMBER(), LEAD(), LAG(), PARTITION BY, and complex groupings.
Performance Tuning and Indexing
Query optimization, execution plans, indexes, and best practices for efficient data access.
ETL and Data Transformation
SQL for Extract, Transform, Load (ETL) processes, data cleaning, and pipeline integration.
Procedures, Transactions, and Security
Stored procedures, triggers, transactions (ACID), error handling, and user/data access control.
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