Structured Query Language (SQL) Fundamentals Training

About This Course

Data is the backbone of modern organisations, and the ability to query and manage it effectively is one of the most in-demand technical skills in today's workplace. Structured Query Language (SQL) is the universal language of relational databases — used by analysts, developers, administrators, and managers across every sector to store, retrieve, and transform data at scale. Whether you are working with customer records, financial transactions, programme monitoring data, or operational logs, SQL is the tool that turns raw data into actionable intelligence.

TrainingComplex's SQL Fundamentals Training is a ten-day, hands-on programme designed to take participants from the very basics of database concepts through to confident, practical SQL usage in real-world scenarios. The course is structured progressively — beginning with the principles of relational databases and the SELECT statement, then building through filtering, sorting, grouping, multi-table joins, subqueries, data modification, and finally database design and administration fundamentals.

Each day combines clear conceptual instruction with guided lab exercises performed on live database environments, ensuring that every topic is immediately reinforced through practice. Participants work with realistic datasets drawn from business, public sector, and development contexts, making the learning directly applicable to their own professional environments. By the close of the programme, every participant will have built a working portfolio of SQL queries and scripts that they can take back and use on the job from day one.

This programme is suitable for absolute beginners with no prior SQL experience as well as for professionals who have used SQL informally and want to consolidate and deepen their knowledge. TrainingComplex's expert facilitators bring both technical depth and strong instructional design to ensure the material is accessible, rigorous, and immediately useful.

Who Should Attend

Data analysts and business intelligence professionals seeking to build or formalise their SQL skills
Finance and accounting staff who work with large datasets and need to query financial databases
Monitoring and evaluation officers who manage programme data in relational database systems
ICT officers and system administrators responsible for database maintenance and reporting
Software developers and application support staff working with backend database systems
Project managers and operations staff who need to extract and interpret data independently
Research and statistics professionals handling large structured datasets
Public sector employees working with government data management systems
Recent graduates and early-career professionals entering data-related roles

Learning Objectives

Explain the principles of relational database management systems and how data is organised in tables
Write accurate SELECT statements to retrieve specific data from single and multiple tables
Apply WHERE clauses, comparison operators, and logical operators to filter query results precisely
Use ORDER BY, GROUP BY, and HAVING clauses to sort and aggregate data effectively
Perform INNER, LEFT, RIGHT, and FULL OUTER JOINs to combine data from related tables
Write subqueries and nested queries to solve complex data retrieval problems
Use built-in SQL functions for string manipulation, date handling, and numeric calculations
Insert, update, and delete records safely using DML statements with appropriate constraints
Design normalised relational database schemas using primary keys, foreign keys, and indexes
Create and manage database objects including tables, views, and stored procedures
Apply transactions and understand basic concurrency control to protect data integrity
Optimise query performance through indexing strategies and query execution plan analysis
Apply SQL best practices for security, data quality, and maintainable code in professional settings

Course Modules

Module 1: Introduction to Relational Databases and the SQL Environment

What is a relational database management system (RDBMS) and how it differs from spreadsheets
Key concepts: tables, rows, columns, primary keys, and foreign keys
Overview of popular SQL platforms: MySQL, PostgreSQL, Microsoft SQL Server, and SQLite
Setting up the training environment and running your first SQL statement
How SQL is structured into sub-languages: DQL, DML, DDL, and DCL and what each governs
Understanding schemas and how databases organise multiple tables into logical namespaces

Module 2: Retrieving Data with SELECT

Basic SELECT syntax: selecting all columns versus specific columns
Using column aliases to make output readable and meaningful
Eliminating duplicate rows with DISTINCT
Introduction to the FROM clause and understanding table structure
Controlling the number of rows returned using TOP, LIMIT, or FETCH FIRST depending on the platform
Using literal values and simple expressions inside the SELECT list to extend retrieved data

Module 3: Filtering and Sorting Query Results

Writing WHERE clauses with comparison operators (=, <>, <, >, BETWEEN, IN, LIKE)
Combining conditions with AND, OR, and NOT logical operators
Handling NULL values with IS NULL and IS NOT NULL
Ordering results with ORDER BY in ascending and descending sequence
Using wildcard patterns with LIKE and understanding the difference between % and _ placeholders
Precedence rules for logical operators and using parentheses to enforce evaluation order

Module 4: Aggregating and Grouping Data

Using aggregate functions: COUNT, SUM, AVG, MIN, and MAX
Grouping results with GROUP BY to produce summary reports
Filtering aggregated results with the HAVING clause
Difference between WHERE and HAVING and when to use each
Using COUNT(column) versus COUNT(*) and how NULL values affect aggregate calculations
Rolling up multiple grouping levels with ROLLUP to generate subtotals and grand totals

Module 5: Working with Multiple Tables: JOINs

Understanding relationships between tables and why joins are necessary
INNER JOIN: retrieving only matching rows from two tables
LEFT, RIGHT, and FULL OUTER JOINs: handling non-matching rows
Self-joins and joining more than two tables in a single query
Using table aliases to keep multi-table queries readable and unambiguous
CROSS JOINs and when a Cartesian product is intentionally useful versus a common mistake to avoid

Module 6: Subqueries and Derived Tables

Writing single-row and multi-row subqueries in the WHERE clause
Using subqueries in the SELECT list and the FROM clause as derived tables
Correlated subqueries and how they differ from independent subqueries
Using EXISTS and NOT EXISTS to test for the presence of related records
Rewriting subqueries as JOINs and understanding when each approach is preferable for clarity and performance
Using Common Table Expressions (CTEs) with the WITH clause as a readable alternative to nested derived tables

Module 7: Built-in SQL Functions

String functions: CONCAT, UPPER, LOWER, TRIM, SUBSTRING, and REPLACE
Date and time functions: GETDATE, DATEPART, DATEDIFF, and formatting date output
Numeric functions: ROUND, ABS, CEILING, FLOOR, and CAST for type conversion
Conditional logic with CASE WHEN expressions to create calculated columns
Using COALESCE and NULLIF to handle NULL values gracefully within expressions
Understanding function portability: noting where syntax differs across MySQL, PostgreSQL, and SQL Server

Module 8: Modifying Data with DML Statements

Inserting single and multiple rows with INSERT INTO statements
Updating existing records with UPDATE and targeted WHERE conditions
Deleting records safely with DELETE and understanding truncation versus deletion
Using transactions (BEGIN, COMMIT, ROLLBACK) to protect data during modifications
Using INSERT INTO … SELECT to populate a table from query results in a single statement
Understanding the risks of UPDATE and DELETE without a WHERE clause and strategies for testing changes before committing

Module 9: Database Design and Normalisation

Principles of normalisation: first, second, and third normal form explained
Designing entity-relationship (ER) diagrams to plan database structure
Defining constraints: PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, and CHECK
Creating, altering, and dropping tables using DDL statements
Choosing appropriate data types for columns and the impact of data type choice on storage and query accuracy
Understanding referential integrity and how cascading actions (ON DELETE CASCADE, ON UPDATE CASCADE) maintain consistency across related tables

Module 10: Views, Indexes, and Database Objects

Creating and managing views to simplify complex queries and control data access
Understanding indexes: how they work and when to create them for performance
Introduction to stored procedures: writing and executing reusable SQL code blocks
Using sequences and auto-increment columns for surrogate key generation
Difference between updatable and non-updatable views and the implications for using views as data access layers
Introduction to triggers: automating actions in response to INSERT, UPDATE, or DELETE events on a table

Module 11: Query Performance and Optimisation

Reading and interpreting a query execution plan to identify bottlenecks
Indexing strategies: clustered versus non-clustered indexes and composite indexes
Avoiding common performance pitfalls: SELECT *, implicit conversions, and functions on indexed columns
Rewriting inefficient queries using best-practice patterns
Understanding statistics and how the query optimiser uses them to choose execution plans
Using query hints and the impact of index fragmentation on ongoing database performance

Module 12: SQL Security, Data Quality, and Best Practices

User roles, permissions, and the principle of least privilege in database security
Preventing SQL injection: parameterised queries and input validation concepts
Data quality checks: using SQL to identify duplicates, nulls, and out-of-range values
Code readability and maintainability: formatting conventions, commenting, and naming standards
Using GRANT and REVOKE statements to manage object-level permissions for users and roles
Auditing and logging strategies: tracking who accessed or modified data and why audit trails matter for compliance

Module 13: Capstone Project and Real-World Application

Capstone scenario briefing: participants receive a realistic business dataset and a set of analytical questions to answer
Schema design and data loading: structuring tables, applying constraints, and importing data
Query development: writing and refining queries to answer each business question
Presentation and peer review: sharing solutions, discussing alternative approaches, and consolidating key lessons from the programme
Performance and quality review: applying optimisation techniques and data quality checks learned throughout the course to the capstone dataset
Reflective self-assessment and next steps: identifying personal skill gaps, exploring advanced SQL topics, and mapping a learning path for continued development

Requirements & Prerequisites

No prior SQL or programming experience is required to attend this course. Participants should be comfortable using a computer, navigating file systems, and working with spreadsheet applications such as Microsoft Excel. A basic familiarity with the concept of tables and rows of data — as encountered in spreadsheets or simple databases — will be helpful but is not a formal prerequisite.

Training Methodology

Instructor-led demonstrations on a live database environment, with participants following along on individual workstations or laptops
Guided lab exercises after each conceptual segment, allowing participants to write and run SQL queries against realistic sample datasets
Progressive challenge sets that start with simple retrieval tasks and build toward multi-table, multi-condition queries
Peer debugging sessions where participants review each other's queries, discuss errors, and learn to read SQL error messages systematically
Case study scenarios drawn from business, public sector, and development programme contexts to anchor SQL concepts in familiar professional situations
Query-building workshops where small groups collaborate to solve a defined data problem, then present and compare their approaches
A running personal query library that each participant builds throughout the ten days, creating a practical reference they take away
End-of-day reflection and Q&A reviews to consolidate learning and address common misconceptions before the next session
A capstone project on the final day requiring participants to design a schema, load data, and answer a set of business questions using SQL alone

Organisational Benefits

Organisations gain staff who can independently query and analyse operational data without relying solely on IT departments
Data-driven decision-making is accelerated as employees can extract and interpret information directly from source systems
Data quality and integrity improve as staff understand how databases work and how to handle data responsibly
Reporting cycles are shortened when analysts can write their own queries rather than submitting requests through intermediaries
Cost savings are achieved by reducing dependence on external consultants for routine data extraction and reporting tasks
Monitoring, evaluation, and accountability functions are strengthened through better access to programme and operational data
ICT teams benefit from colleagues who understand database concepts, reducing support burden and miscommunication
Organisations build internal capacity that supports digital transformation initiatives and data governance frameworks
Staff confidence and professional competence increase, contributing to employee satisfaction and retention

Where Is Structured Query Language (SQL) Fundamentals Training Offered?

This course runs in-person across: Kampala, Johannesburg, Naivasha, Accra, Dar es Salaam, Pretoria, Arusha, Kisumu, Addis Ababa, Nakuru, Dubai, Abuja, Nairobi, Zanzibar, Cape Town, Riyadh, Mombasa, Lagos, Kigali, plus Live Virtual (online) cohorts. Browse live dates for your city below.

Upcoming Schedules

Location	Format	Dates	Price
Live Virtual	Online	12 Sept 2026 – 1 Nov 2026	KES 160,000
Kampala, Uganda	In-Person	28 Sept 2026 – 7 Oct 2026	USD 3,800
Johannesburg, South Africa	In-Person	28 Sept 2026 – 7 Oct 2026	USD 7,000
Naivasha, Kenya	In-Person	28 Sept 2026 – 7 Oct 2026	KES 240,000
Accra, Ghana	In-Person	28 Sept 2026 – 7 Oct 2026	USD 7,600
Dar es Salaam, Tanzania	In-Person	28 Sept 2026 – 7 Oct 2026	USD 4,600
Accra, Ghana	In-Person	5 Oct 2026 – 14 Oct 2026	USD 7,600
Johannesburg, South Africa	In-Person	5 Oct 2026 – 14 Oct 2026	USD 7,000
Naivasha, Kenya	In-Person	5 Oct 2026 – 14 Oct 2026	KES 240,000
Dar es Salaam, Tanzania	In-Person	5 Oct 2026 – 14 Oct 2026	USD 4,600
Kampala, Uganda	In-Person	5 Oct 2026 – 14 Oct 2026	USD 3,800
Pretoria, South Africa	In-Person	12 Oct 2026 – 21 Oct 2026	USD 6,600
Arusha, Tanzania	In-Person	12 Oct 2026 – 21 Oct 2026	USD 4,200
Kisumu, Kenya	In-Person	12 Oct 2026 – 21 Oct 2026	KES 240,000
Addis Ababa, Ethiopia	In-Person	12 Oct 2026 – 21 Oct 2026	USD 4,800

+243 more dates — view live schedule →

Frequently Asked Questions

Do I need any prior programming or database experience to attend?

No prior experience is required. This course is designed for complete beginners and assumes no knowledge of SQL or programming. All you need is comfort using a computer and working with data in a spreadsheet-like environment.

What software or tools will be used during the training?

The course uses industry-standard SQL platforms — primarily MySQL and PostgreSQL — which are free and open-source. All necessary software will be pre-configured in the training environment, and participants will receive installation guides if they wish to set up the tools on their own machines.

Will I receive a certificate upon completion?

Yes. Participants who attend the full ten-day programme and complete the capstone project will receive a TrainingComplex Certificate of Completion in SQL Fundamentals, which can be shared with employers and added to professional profiles.

Is this course suitable for non-technical professionals such as analysts or M&E officers?

Absolutely. The course is specifically designed to be accessible to professionals from non-IT backgrounds, including data analysts, finance staff, and monitoring and evaluation officers. The examples and case studies are drawn from business and public sector contexts that resonate with non-developer audiences.

Will participants have access to course materials after the training ends?

Yes. All participants receive a comprehensive course workbook, a copy of their personal query library built during the programme, and access to the sample datasets used in the labs, so they can continue practising and referring to materials after they return to their organisations.

View Live Schedule & Book →