Advanced Querying Microsoft SQL Server with Transact-SQL

Take your SQL skills to the next level

Master advanced SQL concepts with Microsoft’s Transact-SQL. Develop your confidence writing complex queries, managing indexes and exploring metadata, and run your databases more efficiently. By the end of the course, you’ll be equipped to write more sophisticated code and support data-driven decision-making more effectively. 

Learning objectives
  • Create and use views 
  • Use common table expressions 
  • Apply pivoting and enhanced grouping 
  • Work with windowing functions 
  • Create and manage tables 
  • Use sequences and synonyms 
  • Create and manage indexes 
  • Extract schema metadata 
  • Improve query performance 

What you’ll learn

Learn how to run efficient, complex queries with advanced Transact-SQL features such as windowing functions, pivoting, indexing strategies, metadata extraction and performance tuning for large-scale data environments. Develop the skills to write optimised SQL that delivers faster results and supports smarter decision-making. 

Simplifying logic with table expressions

Master the use of table expressions to make your SQL code more readable, maintainable and efficient. You’ll learn how to simplify complex logic by structuring it into manageable components using views, inline table-valued functions and derived tables. These techniques are especially valuable when working with nested queries or building solutions that need to adapt to evolving data requirements. 

Advanced analytics with windowing functions

Unlock new analytical capabilities in your SQL queries by using windowing functions. You’ll learn how to apply ranking, aggregate and offset functions to perform row-by-row calculations without disrupting the structure of your result set. This includes identifying patterns, calculating running totals, comparing values across rows, and segmenting data into logical partitions. 

Optimising performance with indexes and metadata

Deepen your understanding of indexing and metadata to improve the efficiency of your SQL queries. You’ll explore different index types, including filtered indexes and those applied to views, and learn how each can influence performance. In addition, you’ll work with metadata using both information_schema and system views, gaining the ability to retrieve and interpret schema details and support database troubleshooting. 

What’s included
  • 2 days of instructor-led training in a live virtual classroom 
  • Interactive hands-on live labs 
  • All relevant course materials 
  • Course completion certificate 

Key facts

Ideal for

IT professionals and skilled data users who want to understand advanced querying techniques beyond basic SQL 

Prerequisites

You’ll need to have solid working knowledge of SQL and practical experience in writing queries. 

Learning experience

Our experienced trainers and interactive labs create a focused, practical environment – so you can put theory into practice from day one. 

FAQs

Covering T-SQL techniques including views, indexes, table expressions, and more, this course is ideal for those with a good grounding in SQL. 

What prior experience do I need for the Advanced Querying Microsoft SQL Server with Transact-SQL course?

You’ll need hands-on experience with basic SQL queries. Ideally, you will have already completed our Querying Microsoft SQL Server with Transact-SQL course or have equivalent knowledge. 

What is advanced Transact-SQL and how is it different from basic SQL?

Advanced Transact-SQL (T-SQL) builds on the foundational elements of SQL by introducing more sophisticated features and techniques used for querying Microsoft SQL Server databases. While basic SQL covers commands such as select, insert, update, and delete, advanced T-SQL goes further, enabling you to write complex logic using common table expressions (CTEs), window functions, table-valued functions, and enhanced grouping techniques like rollup and cube. 

What are window functions in SQL and when should I use them?

Window functions in SQL allow you to perform calculations across rows that are related to the current row without collapsing the result set. Unlike aggregate functions, which summarise data into single rows, window functions retain individual row-level detail while enabling running totals, rankings, moving averages, and value comparisons. Common window functions include rank, row number, lead, lag and sum over a defined window. 

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