SQL for Data Analysis - Advanced

  • Length 1 day
Course overview
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Why study this course

A crucial skill for anyone working with data is the ability to access and analyse that data. Structured Query Language (SQL) enables users to access data from databases, combine data from multiple related tables and to aggregate, sort, filter, or limit the data retrieved as needed. This advanced course builds upon the skills learnt in our SQL for Data Analysis - Intermediate course.

In this course, students will use more sophisticated techniques for querying databases and reshaping and manipulating result sets. Participants will learn to reshape data by pivoting and unpivoting. They will write more complex queries using subqueries, temporary tables, and common table expressions. They will use recursive techniques to query hierarchical data and create date dimension tables. Students will build on their understanding of scalar user-defined functions and local variables to create table-valued functions and use table variables.

Students will also learn to simplify querying and increase their efficiency by using views and stored procedures. Students work with an Azure SQL database and write queries in Microsoft’s Transact-SQL (T-SQL). Much of what is covered will be useful for users working with other database products.

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What you’ll learn

Upon completion of this course students will be able to:

  • use more sophisticated techniques for querying databases

  • reshape and manipulate result sets

  • reshape data by pivoting and unpivoting

  • write more complex queries using subqueries, temporary tables and common table expressions

  • use recursive techniques to query hierarchical data and create date dimension tables

  • write more efficient SQL code


SQL at Lumify Work

A crucial skill for anyone working with data is the ability to access and analyse that data. Structured Query Language (SQL) enables users to access data from databases; to combine data from multiple related tables; and to aggregate, sort, filter, or limit the data retrieved as needed. The knowledge you gain at SQL training could mean the difference between failing, meeting, and exceeding goals.


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Course subjects

Introduction

  • SQL and T-SQL

Reshaping data

  • Use PIVOT to turn rows into columns

  • Use UNPIVOT to rotate columns into rows

Writing More Complex Queries

  • Subqueries

  • Local and global temporary tables

  • Create, modify, and delete temporary tables

  • Common table expressions

  • Nested CTEs

  • Recursive CTEs

  • Query hierarchical data

  • Create date dimension tables

More Complex Joins

  • Cross joins

  • Self joins

  • Anti joins

  • Semi joins

Variables

  • Local variables

  • Table variables

  • Temporary tables vs CTEs vs table variables

User-Defined Functions

  • Scalar user-defined functions

  • Table-valued functions

  • Multi-statement table-valued functions

  • Schemas

  • Use APPLY to join output from table-valued functions to a table

Control of Flow

  • IF…ELSE

  • BEGIN…END

Simplifying Code Reuse

  • Working with views

  • Table-valued functions

  • Working with stored procedures

  • Executing stored procedures with parameters

Query Performance

  • Improving query performance

  • Basic principles

  • View execution plans

  • Temporary tables, views, CTEs, and table variables

  • Functions

  • Reusing code


Prerequisites

This course builds on the knowledge gained and skills taught in our SQL for Data Analysis - Intermediate course.

Students attending this course should have completed our Beginner and Intermediate courses or be very familiar with writing SQL queries.


Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.


Request Course Information

By submitting an enquiry, you agree to our privacy policy and receiving email and other forms of communication from us. You can opt-out at any time.