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Course Features

Price

Original price was: £490.00.Current price is: £14.99.

Study Method

Online | Self-paced

Course Format

Reading Material - PDF, article

Duration

1 day, 14 hours

Qualification

No formal qualification

Certificate

At completion

Additional info

Coming soon

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Modern workspace showing PostgreSQL dashboards, query editors, charts, and tables representing SQL data analysis concepts

Overview

SQL Data Analysis is a core skill for anyone working with data, databases, or business intelligence in today’s data-driven world. This masterclass is designed to take learners from SQL fundamentals to advanced analytical and database development techniques using PostgreSQL, one of the most powerful and widely used relational database systems.

Throughout the course, learners build strong foundations in querying data, filtering results, sorting records, and aggregating information for meaningful insights. As the course progresses, students gain hands-on experience with joins, subqueries, window functions, and advanced grouping techniques that are essential for real-world SQL data analysis tasks. Practical exercises and challenges reinforce learning, while structured projects help translate theory into job-ready skills.

In addition to analytics, the course covers critical database development concepts such as table creation, constraints, indexing, views, stored procedures, transactions, and user management in PostgreSQL. Learners also explore query optimisation, execution plans, and performance improvement strategies to ensure efficient and scalable database solutions. By the end of the course, students will be confident working with complex datasets, building analytical reports, and managing relational databases professionally.

This course balances clarity, depth, and practical application, making it suitable for both career advancement and academic development. Learners receive a free course completion certificate upon finishing the programme. For those who require formal documentation, multiple premium certificate and transcript options are available for purchase. Students also benefit from 5-star rated support available 24/7 via email, ensuring guidance whenever it is needed.

This course is ideal for aspiring data analysts, database developers, business intelligence professionals, and students seeking strong SQL skills. It also suits professionals in finance, marketing, operations, or IT who work with data and want to improve their analytical capabilities using structured databases.
No advanced background is required. Basic computer literacy is sufficient, and prior exposure to spreadsheets or data concepts is helpful but not essential. Learners should be comfortable installing software and willing to practise regularly to gain maximum benefit from hands-on SQL exercises.
After completion, learners can pursue roles such as data analyst, junior database developer, reporting analyst, business intelligence analyst, or SQL developer. The skills also support progression into data science, data engineering, and postgraduate study in data-focused or technology-driven fields.

Who is this course for?

SQL Data Analysis is a core skill for anyone working with data, databases, or business intelligence in today’s data-driven world. This masterclass is designed to take learners from SQL fundamentals to advanced analytical and database development techniques using PostgreSQL, one of the most powerful and widely used relational database systems.

Throughout the course, learners build strong foundations in querying data, filtering results, sorting records, and aggregating information for meaningful insights. As the course progresses, students gain hands-on experience with joins, subqueries, window functions, and advanced grouping techniques that are essential for real-world SQL data analysis tasks. Practical exercises and challenges reinforce learning, while structured projects help translate theory into job-ready skills.

In addition to analytics, the course covers critical database development concepts such as table creation, constraints, indexing, views, stored procedures, transactions, and user management in PostgreSQL. Learners also explore query optimisation, execution plans, and performance improvement strategies to ensure efficient and scalable database solutions. By the end of the course, students will be confident working with complex datasets, building analytical reports, and managing relational databases professionally.

This course balances clarity, depth, and practical application, making it suitable for both career advancement and academic development. Learners receive a free course completion certificate upon finishing the programme. For those who require formal documentation, multiple premium certificate and transcript options are available for purchase. Students also benefit from 5-star rated support available 24/7 via email, ensuring guidance whenever it is needed.

This course is ideal for aspiring data analysts, database developers, business intelligence professionals, and students seeking strong SQL skills. It also suits professionals in finance, marketing, operations, or IT who work with data and want to improve their analytical capabilities using structured databases.
No advanced background is required. Basic computer literacy is sufficient, and prior exposure to spreadsheets or data concepts is helpful but not essential. Learners should be comfortable installing software and willing to practise regularly to gain maximum benefit from hands-on SQL exercises.
After completion, learners can pursue roles such as data analyst, junior database developer, reporting analyst, business intelligence analyst, or SQL developer. The skills also support progression into data science, data engineering, and postgraduate study in data-focused or technology-driven fields.

Requirements

SQL Data Analysis is a core skill for anyone working with data, databases, or business intelligence in today’s data-driven world. This masterclass is designed to take learners from SQL fundamentals to advanced analytical and database development techniques using PostgreSQL, one of the most powerful and widely used relational database systems.

Throughout the course, learners build strong foundations in querying data, filtering results, sorting records, and aggregating information for meaningful insights. As the course progresses, students gain hands-on experience with joins, subqueries, window functions, and advanced grouping techniques that are essential for real-world SQL data analysis tasks. Practical exercises and challenges reinforce learning, while structured projects help translate theory into job-ready skills.

In addition to analytics, the course covers critical database development concepts such as table creation, constraints, indexing, views, stored procedures, transactions, and user management in PostgreSQL. Learners also explore query optimisation, execution plans, and performance improvement strategies to ensure efficient and scalable database solutions. By the end of the course, students will be confident working with complex datasets, building analytical reports, and managing relational databases professionally.

This course balances clarity, depth, and practical application, making it suitable for both career advancement and academic development. Learners receive a free course completion certificate upon finishing the programme. For those who require formal documentation, multiple premium certificate and transcript options are available for purchase. Students also benefit from 5-star rated support available 24/7 via email, ensuring guidance whenever it is needed.

This course is ideal for aspiring data analysts, database developers, business intelligence professionals, and students seeking strong SQL skills. It also suits professionals in finance, marketing, operations, or IT who work with data and want to improve their analytical capabilities using structured databases.
No advanced background is required. Basic computer literacy is sufficient, and prior exposure to spreadsheets or data concepts is helpful but not essential. Learners should be comfortable installing software and willing to practise regularly to gain maximum benefit from hands-on SQL exercises.
After completion, learners can pursue roles such as data analyst, junior database developer, reporting analyst, business intelligence analyst, or SQL developer. The skills also support progression into data science, data engineering, and postgraduate study in data-focused or technology-driven fields.

Career path

SQL Data Analysis is a core skill for anyone working with data, databases, or business intelligence in today’s data-driven world. This masterclass is designed to take learners from SQL fundamentals to advanced analytical and database development techniques using PostgreSQL, one of the most powerful and widely used relational database systems.

Throughout the course, learners build strong foundations in querying data, filtering results, sorting records, and aggregating information for meaningful insights. As the course progresses, students gain hands-on experience with joins, subqueries, window functions, and advanced grouping techniques that are essential for real-world SQL data analysis tasks. Practical exercises and challenges reinforce learning, while structured projects help translate theory into job-ready skills.

In addition to analytics, the course covers critical database development concepts such as table creation, constraints, indexing, views, stored procedures, transactions, and user management in PostgreSQL. Learners also explore query optimisation, execution plans, and performance improvement strategies to ensure efficient and scalable database solutions. By the end of the course, students will be confident working with complex datasets, building analytical reports, and managing relational databases professionally.

This course balances clarity, depth, and practical application, making it suitable for both career advancement and academic development. Learners receive a free course completion certificate upon finishing the programme. For those who require formal documentation, multiple premium certificate and transcript options are available for purchase. Students also benefit from 5-star rated support available 24/7 via email, ensuring guidance whenever it is needed.

This course is ideal for aspiring data analysts, database developers, business intelligence professionals, and students seeking strong SQL skills. It also suits professionals in finance, marketing, operations, or IT who work with data and want to improve their analytical capabilities using structured databases.
No advanced background is required. Basic computer literacy is sufficient, and prior exposure to spreadsheets or data concepts is helpful but not essential. Learners should be comfortable installing software and willing to practise regularly to gain maximum benefit from hands-on SQL exercises.
After completion, learners can pursue roles such as data analyst, junior database developer, reporting analyst, business intelligence analyst, or SQL developer. The skills also support progression into data science, data engineering, and postgraduate study in data-focused or technology-driven fields.

    • Welcome & Course Overview 00:10:00
    • Why Learn SQL in 2025 00:10:00
    • How this course works 00:10:00
    • What is a Database & How SQL Works 00:10:00
    • Understanding SQL Dialects 00:10:00
    • Installing PostgreSQL & pgAdmin on Windows 00:10:00
    • Installing PostgreSQL & pgAdmin on MacOS 00:10:00
    • Setting Up Your First Database 00:10:00
    • Course Project Introduction 00:10:00
    • Writing Your First SELECT Statement 00:10:00
    • Challenge – SELECT Queries 00:10:00
    • Solution – SELECT Queries 00:10:00
    • Sorting Data with ORDER BY 00:10:00
    • Challenge – ORDER BY 00:10:00
    • Solution – ORDER BY 00:10:00
    • Using SELECT DISTINCT to Remove Duplicates 00:10:00
    • Challenge – SELECT DISTINCT 00:10:00
    • Solution – SELECT DISTINCT 00:10:00
    • Applying LIMIT 00:10:00
    • COUNT() Functions 00:10:00
    • Daily Practice Challenges 00:10:00
    • Day Summary & Key Takeaways 00:10:00
    • Understanding the WHERE Clause 00:10:00
    • Challenge – Filtering with WHERE 00:10:00
    • Solution – Filtering with WHERE 00:10:00
    • Using Comparison and Logical Operators (=, >, <, !=) 00:10:00
    • Challenge – WHERE Operators 00:10:00
    • Solution – WHERE Operators 00:10:00
    • Combining Conditions with AND and OR 00:10:00
    • Challenge – AND / OR Conditions 00:10:00
    • Solution – AND / OR Conditions 00:10:00
    • Filtering with BETWEEN for Ranges 00:10:00
    • Challenge – BETWEEN Clause 00:10:00
    • Solution – BETWEEN Clause 00:10:00
    • Using IN for Multiple Matches 00:10:00
    • Challenge – IN Operator 00:10:00
    • Solution – IN Operator 00:10:00
    • Pattern Matching with LIKE and Wildcards 00:10:00
    • Challenge – LIKE Operator 00:10:00
    • Solution – LIKE Operator 00:10:00
    • Using Comments and Column Aliases for Readability 00:10:00
    • Daily Practice Challenges 00:10:00
    • Day Summary & Key Takeaways 00:10:00
    • Lecture Overview – Today’s Plan 00:10:00
    • Using Aggregate Functions (SUM, AVG, COUNT, MIN, MAX) 00:10:00
    • Challenge – Aggregate Functions 00:10:00
    • Grouping Data with GROUP BY 00:10:00
    • Challenge – GROUP BY 00:10:00
    • Solution – GROUP BY 00:10:00
    • GROUP BY Multiple Columns 00:10:00
    • Challenge – GROUP BY Multiple Columns 00:10:00
    • Solution – GROUP BY Multiple Columns 00:10:00
    • Filtering Grouped Data with HAVING 00:10:00
    • Challenge – HAVING Clause 00:10:00
    • Solution – HAVING Clause 00:10:00
    • Introducing Project 2 – Sales Summary Analysis 00:10:00
    • Day Summary & Key Takeaways 00:10:00
    • Lecture Overview – Today’s Plan 00:10:00
    • Using LENGTH, LOWER and UPPER Functions 00:10:00
    • Challenge – LENGTH, LOWER & UPPER 00:10:00
    • Solution – LENGTH, LOWER & UPPER 00:10:00
    • Extracting Text with LEFT and RIGHT 00:10:00
    • Challenge – LEFT and RIGHT 00:10:00
    • Solution – LEFT and RIGHT 00:10:00
    • Concatenating Strings with CONCAT and || Operator 00:10:00
    • Challenge – Concatenation 00:10:00
    • Solution – Concatenation 00:10:00
    • Finding Character Positions with POSITION() 00:10:00
    • Challenge – POSITION() 00:10:00
    • Solution – POSITION() 00:10:00
    • Extracting Substrings with SUBSTRING() 00:10:00
    • Challenge – SUBSTRING() 00:10:00
    • Solution – SUBSTRING() 00:10:00
    • Working with Dates using EXTRACT() 00:10:00
    • Challenge – EXTRACT() 00:10:00
    • Solution – EXTRACT() 00:10:00
    • Formatting Dates with TO_CHAR() 00:10:00
    • Challenge – TO_CHAR() 00:10:00
    • Solution – TO_CHAR() 00:10:00
    • Handling Intervals and Timestamps 00:10:00
    • Challenge – Intervals & Timestamps 00:10:00
    • Solution – Intervals & Timestamps 00:10:00
    • Using Mathematical Functions and Operators 00:10:00
    • Challenge – Mathematical Functions and Operators 00:10:00
    • Solution – Mathematical Functions and Operators 00:10:00
    • Understanding CASE WHEN Expressions (Theory) 00:10:00
    • CASE WHEN Hands-On Examples 00:10:00
    • Challenge – CASE WHEN Scenarios 00:10:00
    • Solution – CASE WHEN Challenges 00:10:00
    • Using CASE WHEN with Aggregate Functions (SUM, AVG) 00:10:00
    • Handling NULL Values with COALESCE() 00:10:00
    • Converting Data Types with CAST() 00:10:00
    • Challenge – CAST & COALESCE 00:10:00
    • Solution – CAST & COALESCE 00:10:00
    • Replacing Text Values with REPLACE() 00:10:00
    • What Are Joins and Why They Matter 00:10:00
    • INNER JOIN Concept and Syntax (Theory) 00:10:00
    • Hands-On – INNER JOIN Practice 00:10:00
    • Challenge – INNER JOIN 00:10:00
    • Solution – INNER JOIN 00:10:00
    • Understanding FULL OUTER JOIN 00:10:00
    • Combining JOIN with WHERE Conditions 00:10:00
    • LEFT OUTER JOIN Explained 00:10:00
    • Challenge – LEFT OUTER JOIN 00:10:00
    • Solution – LEFT OUTER JOIN 00:10:00
    • RIGHT OUTER JOIN Overview 00:10:00
    • Challenge – Join Exercises 00:10:00
    • Solution – Join Exercises 00:10:00
    • Joins on Multiple Conditions 00:10:00
    • Solution – Joins on Multiple Conditions 00:10:00
    • Joining Multiple Tables Together 00:10:00
    • Practice – Multi-Table Joins 00:10:00
    • Challenge – Joining Multiple Tables 00:10:00
    • Solution – Joining Multiple Tables 00:10:00
    • Merging Results with UNION and UNION ALL 00:10:00
    • Practice – UNION Examples 00:10:00
    • Creating Subqueries in WHERE Clauses 00:10:00
    • Challenge – Subqueries in WHERE 00:10:00
    • Solution – Subqueries in WHERE 00:10:00
    • Additional Subquery Challenges (WHERE) 00:10:00
    • Solution – Advanced Subquery Examples 00:10:00
    • Using Subqueries in FROM Clauses 00:10:00
    • Challenge – Subqueries in FROM 00:10:00
    • Solution – Subqueries in FROM 00:10:00
    • Applying Subqueries in SELECT Statements 00:10:00
    • Challenge – Subqueries in SELECT 00:10:00
    • Solution – Subqueries in SELECT 00:10:00
    • Understanding Correlated Subqueries in WHERE 00:10:00
    • Challenge – Correlated Subqueries in WHERE 00:10:00
    • Solution – Correlated Subqueries in WHERE 00:10:00
    • Correlated Subqueries in SELECT Statements 00:10:00
    • Additional Correlated Subquery Challenges 00:10:00
    • Solution – Advanced Correlated Subqueries 00:10:00
    • Project Introduction & Dataset Overview 00:10:00
    • Solution 1 – Exploring the Dataset 00:10:00
    • Solution 2 – Filtering and Sorting Data 00:10:00
    • Solution 3 – Aggregating Data with GROUP BY 00:10:00
    • Solution 4 – Using Conditional Logic (CASE WHEN) 00:10:00
    • Solution 5 – Joining Multiple Tables 00:10:00
    • Solution 6 – Applying Subqueries for Insights 00:10:00
    • Solution 7 – Using String and Date Functions 00:10:00
    • Solution 8 – Calculating Key Metrics with Aggregates 00:10:00
    • Solution 9 – Building Analytical Reports 00:10:00
    • Solution 10 – Data Validation and Error Checking 00:10:00
    • Solution 11 – Optimising Query Performance 00:10:00
    • Solution 12 – Creating Views for Reusability 00:10:00
    • Solution 13 – Applying Indexing for Faster Queries 00:10:00
    • Solution 14 – Final Review & Key Takeaways 00:10:00
    • Overview – Managing Databases and Tables 00:10:00
    • Creating a New Database (CREATE DATABASE) 00:10:00
    • Understanding PostgreSQL Data Types 00:10:00
    • Working with Constraints in Tables 00:10:00
    • Defining Primary Keys and Foreign Keys 00:10:00
    • Creating Tables with CREATE TABLE 00:10:00
    • Inserting Records with INSERT 00:10:00
    • Modifying Tables with ALTER TABLE 00:10:00
    • Challenge – ALTER TABLE 00:10:00
    • Solution – ALTER TABLE 00:10:00
    • Removing Data with TRUNCATE and DROP TABLE 00:10:00
    • Using CHECK Constraints for Data Validation 00:10:00
    • Challenge – CHECK Constraints 00:10:00
    • Solution – CHECK Constraints 00:10:00
    • Updating Records with UPDATE 00:10:00
    • Challenge – UPDATE 00:10:00
    • Solution – UPDATE 00:10:00
    • Deleting Records with DELETE 00:10:00
    • Challenge – DELETE 00:10:00
    • Solution – DELETE 00:10:00
    • Creating Tables from Queries with CREATE TABLE AS 00:10:00
    • Challenge – CREATE TABLE AS 00:10:00
    • Solution – CREATE TABLE AS 00:10:00
    • Creating Reusable Views with CREATE VIEW 00:10:00
    • Using CREATE MATERIALIZED VIEW 00:10:00
    • Managing and Refreshing Views 00:10:00
    • Importing and Exporting Data in PostgreSQL 00:10:00
    • Introduction to Window Functions and OVER() 00:10:00
    • Challenge – OVER() with PARTITION BY 00:10:00
    • Solution – OVER() with PARTITION BY 00:10:00
    • Using OVER() with ORDER BY 00:10:00
    • Challenge – OVER() with ORDER BY 00:10:00
    • Solution – OVER() with ORDER BY 00:10:00
    • Ranking Data with RANK() 00:10:00
    • Challenge – RANK() 00:10:00
    • Solution – RANK() 00:10:00
    • Using FIRST_VALUE() for Leading Entries 00:10:00
    • Comparing Rows with LEAD() and LAG() 00:10:00
    • Challenge – LEAD() and LAG() 00:10:00
    • Solution – LEAD() and LAG() 00:10:00
    • Additional Analytical Challenges 00:10:00
    • Solution – Additional Analytical Challenges 00:10:00
    • Understanding GROUPING SETS for Multi-Level Aggregation 00:10:00
    • Challenge – GROUPING SETS 00:10:00
    • Solution – GROUPING SETS 00:10:00
    • Creating Summary Levels with ROLLUP 00:10:00
    • Challenge – ROLLUP 00:10:00
    • Solution – ROLLUP 00:10:00
    • Using CUBE for Comprehensive Aggregations 00:10:00
    • Applying Self Joins to Compare Rows Within the Same Table 00:10:00
    • Challenge – Self Joins 00:10:00
    • Solution – Self Joins 00:10:00
    • Exploring CROSS JOIN for Cartesian Products 00:10:00
    • Understanding NATURAL JOIN and Its Use Cases 00:10:00
    • Introduction to User-Defined Functions (UDFs) 00:10:00
    • Example – Creating and Using a User-Defined Function 00:10:00
    • Challenge – User-Defined Functions 00:10:00
    • Solution – User-Defined Functions 00:10:00
    • Working with Transactions in PostgreSQL 00:10:00
    • Challenge – Transactions 00:10:00
    • Solution – Transactions 00:10:00
    • Understanding Rollbacks and Savepoints 00:10:00
    • Creating Stored Procedures for Automation 00:10:00
    • Challenge – Stored Procedures 00:10:00
    • Solution – Stored Procedures 00:10:00
    • Managing Users and Roles in PostgreSQL 00:10:00
    • Creating Users and Roles with CREATE USER / ROLE 00:10:00
    • Granting and Revoking Privileges (GRANT & REVOKE) 00:10:00
    • Hands-On – Working with Privileges and Permissions 00:10:00
    • Introduction to Indexes and Their Importance 00:10:00
    • Understanding B-Tree Indexes 00:10:00
    • Using Bitmap Indexes for Data Warehousing 00:10:00
    • Indexing Best Practices and Guidelines 00:10:00
    • Creating Indexes in PostgreSQL 00:10:00
    • Reading Execution Plans and Improving Query Performance 00:10:00
    • Exam of SQL for Data Analysis & Database Development Masterclass 00:50:00
    • Premium Certificate 00:15:00
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Yes, our premium certificate and transcript are widely recognized and accepted by embassies worldwide, particularly by the UK embassy. This adds credibility to your qualification and enhances its value for professional and academic purposes.

Yes, this course is designed for learners of all levels, including beginners. The content is structured to provide step-by-step guidance, ensuring that even those with no prior experience can follow along and gain valuable knowledge.

Yes, professionals will also benefit from this course. It covers advanced concepts, practical applications, and industry insights that can help enhance existing skills and knowledge. Whether you are looking to refine your expertise or expand your qualifications, this course provides valuable learning.

No, you have lifetime access to the course. Once enrolled, you can revisit the materials at any time as long as the course remains available. Additionally, we regularly update our content to ensure it stays relevant and up to date.

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Yes, the course includes both assessments and assignments. Your final marks will be determined by a combination of 20% from assignments and 80% from assessments. These evaluations are designed to test your understanding and ensure you have grasped the key concepts effectively.

We are a recognized course provider with CPD, UKRLP, and AOHT membership. The logos of these accreditation bodies will be featured on your premium certificate and transcript, ensuring credibility and professional recognition.

Yes, you will receive a free digital certificate automatically once you complete the course. If you would like a premium CPD-accredited certificate, either in digital or physical format, you can upgrade for a small fee.

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Course Features

Price

Original price was: £490.00.Current price is: £14.99.

Study Method

Online | Self-paced

Course Format

Reading Material - PDF, article

Duration

1 day, 14 hours

Qualification

No formal qualification

Certificate

At completion

Additional info

Coming soon

  • Share

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