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SQL Server Transact SQL Querying assisted by GitHub CoPilot
Rating: 5.0 out of 5(1 rating)
16 students

SQL Server Transact SQL Querying assisted by GitHub CoPilot

In this course we learn how to shape SQL Server Database data for use in analytical processes assisted by GitHub Copilot
Created byMark Manore
Last updated 7/2025
English

What you'll learn

  • Become familiar with the basics of querying SQL Server Databases using Transact-SQL
  • Become familiar with the use of GitHub CoPilot to generate faster Transact-SQL code
  • Experience the value of using Jupyter Books and Notebooks
  • Become familiar with the use of Azure Data Studio
  • Exposure to higher level Copilot prompts

Course content

9 sections • 70 lectures • 9h 46m total length
  • Introduction11:37
  • Install SQL Server11:37
  • Setup GitHub & CoPilot Accounts2:31
  • Install Azure Data Studio & Extensions5:30
  • Install Databases5:13
  • Configure Database Connections3:38
  • Install Jupyter Books1:17
  • ADS Course Orientation16:15
  • Survey Course Case Study5:11
  • WATCH THIS - Course Methodology - VERY IMPORTANT9:37
  • Last word on Methodology9:23

Requirements

  • Some familiarity with relational databases would be useful
  • Some experience with programming
  • Some awareness of AI capabilities

Description

Fundamentally, this course will take you through the basics of querying SQL Server databases using Transact SQL (TSQL) with the assistance of GitHub CoPilot.

The course is divided into the following sections.

A) Orientation and Setup

B) Foundations

C) Builtin Functions and Datatypes

D) Filtering and Ordering

E) FROM Clause

  • Basics

  • with JOINS

F) SubQueries

G) Analytical Functions

  • Grouped Aggregates

  • Set Operators

  • Pivot

  • Window Functions

H) Extra Innings

  • Cornucopia Programming - bringing together various programming elements form the course at large.

  • Data Warehousing - most of the course is conducted using the transactional Adventureworks database. Here we look briefly at coding against a dimensionally modelled data warehouse - AdventureworksDW

  • Query Data Shaping - takes a look at intermediate programming techniques we may employ to output a final result set.

  • Data Shaping Exercise - explores the use of Window functions to facilitate data wrangling like 'deduplication', 'gap detection', 'generate new keys' for a data set, 'trimmed mean'.

  • Voice to Prompt - very brief survey of the possible use of voice to text capabilities in generating AI prompts to generate code.

The programming in all of these sections is facilitated through the use of Azure Data Studio and the use of Jupyter Books and Notebooks.

Through the use of AI prompts, GitHub Copilot generates code that is to be reviewed by the programmer as to its accuracy and functionality.

The combination of learning the 'prompting' and code reviews aids the student in learning the syntax and functionality of TSQL

Who this course is for:

  • Report Writers (like Crystal, SSRS, Power BI, Tableau...)
  • Database Developers
  • ETL Programmers
  • Data Engineers
  • Data Scientists
  • Code Reviewers