Technologies / Data & Analytics

SQL - Advanced Data Processing

This training guides participants through advanced SQL data processing techniques, focusing on creating efficient and scalable database solutions. The program combines deep theoretical understanding with intensive practical workshops where participants learn to design complex queries, optimize performance, and implement advanced data processing patterns. Sessions are conducted in a way that helps understand not only how to write advanced SQL code, but also why certain solutions are more effective than others.

Required Participant Preparation

Before starting the training, participants should have practical experience in writing SQL queries and solid understanding of basic database concepts. Good knowledge of DML operations, basic SQL language constructions, and general understanding of database performance issues is essential. Basic knowledge of relational database theory and experience working with real database systems will also be helpful.

Benefits

Training participants gain in-depth knowledge of advanced SQL techniques and practical skills for their effective use
They will learn methods for optimizing complex queries, techniques for designing efficient data structures, and strategies for implementing analytical solutions
The training also develops the ability to understand and optimize execution plans, the ability to design scalable database solutions, and deep understanding of how different SQL constructions impact system performance
After completing the training, participants will be able to independently design and implement advanced database solutions, optimize existing queries, and effectively work with large datasets

Who is this training for?

This training has been carefully designed for professionals who regularly work with databases and want to take their skills to a higher level

It is particularly valuable for database programmers needing to write efficient analytical queries, application developers working with large datasets, data analysts performing complex business analyses, and solution architects designing database systems

The program is also suitable for ETL specialists and data engineers responsible for data processing and transformation in corporate environments

Training program

Table functions and recursive CTEs
Advanced grouping and aggregation

Optimization and Performance
Execution plan analysis and optimization
Designing efficient indexes
Data partitioning strategies
Statistics management and query optimization
Analytical Data Processing

Business metric calculation techniques

Advanced data transformations
Advanced Patterns and Practices

Hierarchical data handling
JSON and XML processing techniques
Cache mechanisms and materialized views

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Frequently asked questions

What are the prerequisites for this training?

The SQL - Advanced Data Processing training does not require specialized prior knowledge. Basic IT knowledge is sufficient.

What is the format and duration of this training?

The training lasts 3 days and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: This training has been carefully designed for professionals who regularly work with databases and want to take their skills to a higher level; It is particularly valuable for database programmers needing to write efficient analytical queries, application developers working with large datasets, data analysts performing complex business analyses, and solution architects designing database systems; The program is also suitable for ETL specialists and data engineers responsible for data processing and transformation in corporate environments.