Analytics Engineering with dbt

Course Category : Data Management

A specialised programme for building reliable, governed analytical data models with dbt, focusing on SQL-based transformations, data quality, testing, documentation, and analytics lifecycle management.
Duration: 5 Days | Level: Advanced

Introduction

Modern organisations increasingly depend on well-structured analytical layers to transform raw data into consistent and decision-ready information. As cloud data platforms expand and data ecosystems become more complex, analytics engineering has emerged as a discipline combining software engineering practices with analytics and business intelligence requirements.
This course examines analytics engineering through dbt, covering project architecture, data modelling, testing, documentation, dependency management, and version control. It emphasises maintainable and scalable transformation layers while establishing governance and quality practices that support trustworthy analytical data products..

Targeted Audience

Analytics Engineers and Data Engineers
Data and Business Intelligence Analysts
Data Warehouse Developers
Data Platform Engineers
Advanced SQL Developers
Data Quality and Governance Professionals
Data-Driven Digital Transformation Specialists
Data and Analytics Team Leaders

Targeted Skills

Understanding analytics engineering within the modern data ecosystem
Structuring scalable and maintainable dbt projects
Developing modular SQL-based transformation models
Managing dependencies and relationships across data models
Designing data quality and integrity tests
Documenting analytical models and data lineage
Integrating version control into analytics development
Applying governance and maintainability practices to analytical assets

Expected Outcomes

Explain the role of analytics engineering and its relationship with data engineering and data analytics.
Design a logical and structured architecture for dbt projects.
Build analytical data models using layered and reusable modelling principles.
Define model dependencies and manage transformation workflows.
Design tests for data quality, validity, and consistency.
Establish an integrated approach to model and source documentation.
Apply version control and collaborative analytics development principles.
Evaluate governance, deployment, and maintenance requirements for enterprise dbt environments.

Training Topics Index

Evolution of analytics engineering within the modern data stack
Relationship between data engineering, analytics engineering, and business intelligence
Warehouse-based transformation and ETL versus ELT architectures
Core components of the dbt ecosystem and project lifecycle
Principles for maintainable and structured analytical environments

Structuring dbt projects, models, folders, and resources
Source definitions and staging model architecture
Intermediate models and analytical presentation layers
Managing dependencies through ref() and source()
Modular modelling and reusable transformation logic

Testing principles within analytics engineering
Generic and custom testing approaches in dbt
Uniqueness, non-null, and referential integrity validation
Documenting models, columns, and data sources
Understanding data lineage and connecting quality controls to transformation flows

Using Jinja for dynamic and structured SQL logic
Macros for reusable and standardised transformation logic
Materializations and model-building strategies
Git-based version control and change management
Structuring development, testing, and production environments

Principles of scheduling and orchestrating analytical transformations
Dependency and package management within dbt environments
Monitoring, troubleshooting, and transformation failure management
Model governance, naming conventions, ownership, and quality standards
Designing scalable enterprise analytics lifecycle frameworks

Course Features

Updated and Interactive Content
Hypothetical Examples and Case Studies
Pre- and Post-assessments to Measure Impact
Verified Certificate with a QR Verification Code

Analytics Engineering with dbt