Data Engineering · SQL
Query, Combine and Transform Data with SQL
Learn the language used to work with data in almost every organisation, from your first SELECT statement to joins, window functions and the queries data engineers rely on.
- Querying, filtering and sorting data
- Joins and aggregations
- Common table expressions and window functions
- Query performance fundamentals
Course overview
About This Course
SQL is the standard language for querying and managing data in relational databases and data warehouses. This course takes you from the basics of retrieving data to writing the multi-step queries used in analysis and data engineering.
Almost every data role uses SQL daily. Analysts use it to answer questions, data engineers use it to transform and load data, and developers use it inside applications. A strong SQL foundation makes every other data skill easier to learn.
You will learn how relational data is organised, how to filter, join and aggregate it, how to break complex problems into readable steps, and how to write queries that perform well.
SQL is the first step in our Data Engineering learning paths, followed by Python for Data Engineering and then the Azure and AWS data engineering courses.
Who it is for
Who Should Take This Course?
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Beginners in data
You are new to working with data and want to start with the most widely used data skill.
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Students and recent graduates
You want practical SQL skills to support data-related studies or job applications.
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Professionals who work with reports
You use spreadsheets or reports and want to get data directly from databases.
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Aspiring data engineers and analysts
You are starting a data career and need SQL as a foundation.
Learning outcomes
What You Will Learn
By working through the course, you will build towards being able to:
Explain how relational databases organise data in tables, keys and relationships.
Write queries that select, filter, sort and limit data.
Combine tables with inner, outer and self joins and choose the right join for a task.
Summarise data with aggregate functions, GROUP BY and HAVING.
Break complex queries into readable steps with subqueries and common table expressions.
Use window functions for rankings, running totals and comparisons between rows.
Recognise common causes of slow queries and apply basic performance practices.
Curriculum
Course Curriculum
The course is organised into modules. Session order and depth may vary by training arrangement.
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Module 1: Relational data basics
How data is organised in relational databases and how SQL talks to them.
Topics covered include
Practical activity: Explore a sample database and describe how its tables relate to each other.
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Module 2: Querying and filtering
Retrieve exactly the rows and columns you need.
Topics covered include
Practical activity: Answer a set of business questions using filtered queries.
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Module 3: Joins
Bring data from several tables together correctly.
Topics covered include
Practical activity: Combine customer, order and product tables to build a sales view.
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Module 4: Aggregations and grouping
Summarise large amounts of data into useful figures.
Topics covered include
Practical activity: Produce monthly summary figures from sample transaction data.
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Module 5: CTEs and window functions
Write multi-step queries that stay readable.
Topics covered include
Practical activity: Rank products by sales within each category and compare month-on-month changes.
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Module 6: Transformation and performance
Shape data for analysis and keep queries efficient.
Topics covered include
Practical activity: Clean a messy sample dataset and improve the performance of a slow query.
Practical learning
Hands-On Learning
SQL is learned by writing queries. Examples of practical activities include:
Practical work uses sample databases. Ask us which database platform is used in your training arrangement.
- Querying sample business databases
- Answering realistic reporting questions
- Cleaning and transforming messy data
- Reviewing and improving slow queries
Before you start
Prerequisites and Learning Requirements
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Recommended background
No prior programming or database experience is needed.
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Technical prerequisites
Comfort using a computer. Familiarity with spreadsheets is helpful but not required.
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Software and tools
A computer with a reliable internet connection for live online sessions. A database tool or online SQL environment is used for practice. Any additional software or accounts for practical activities will be confirmed when you enquire.
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Prior experience
Suitable as a first course in data.
Learning Format
IT Champion Hub offers live, instructor-led online training and workshops. Formats, duration and schedules vary by course and are not the same for every program.
- Live online sessions led by an instructor
- Practical activities alongside explanations
- Upcoming batches and schedules shared on enquiry
Enquire to find out the formats and upcoming batches available for this course. Enquire about this course
FAQ
Frequently Asked Questions
Do I need programming experience?
No. SQL is often the first technical language people learn for data work, and the course starts from the basics.
Which database will we use?
The SQL taught applies across major relational databases and data warehouses. Ask us which platform is used for practice in your training arrangement.
Are there practical exercises?
Yes. You will write queries against sample databases throughout the course, from simple filters to window functions.
What should I learn after SQL?
Python for Data Engineering is the next step in our Data Engineering learning paths, followed by Azure or AWS Data Engineering.
How can I enquire about upcoming training?
Select Enquire About This Course. The enquiry form will note that you are asking about SQL, and we'll get back to you with upcoming batches and available schedules.
Ready to Explore This Learning Path?
Have questions about the curriculum, prerequisites, or training arrangements? Get in touch with IT Champion Hub to discuss your learning goals.