DBT (Data Build Tool) Training Course

12 Lesson

40 Hours

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igmGuru offers the best dbt Training online worldwide. Our dbt course covers essential modules such as dbt Project Setup, Data Modeling & Transformations, Materializations, Sources & Seeds, Testing & Data Quality, Snapshots, Jinja Macros & Templates, Documentation & Lineage, Deployment & CI/CD, and more. This data build tool training syllabus is crafted by industry experts with over 15 years of experience in data analytics and modern data engineering, with practical hands-on projects. We have successfully trained 350+ professionals globally. Enroll in our Data Build Tool certification course to master analytics engineering skills, streamline data workflows, and prepare for official dbt certification.

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Overview

Prerequisites

Proficient in SQL (SELECT, JOINs, CTEs, aggregations)
Familiar with relational databases (PostgreSQL, Snowflake, BigQuery, etc.)
Understanding of data warehousing concepts (ETL/ELT, star/snowflake schemas)
Basic data modeling knowledge (fact and dimension tables)
Comfortable with command-line tools
Basic version control knowledge (Git)
Optional: Python for advanced macros, BI tools experience, cloud data platform familiarity

Who Should Enroll?

Data Analysts
Data Engineers
BI Developers
Analytics Engineers
Data Scientists
Anyone working with SQL and data warehouses

What You Will Learn

How to set up and configure dbt projects
Writing modular, maintainable SQL models
Implementing data transformations using dbt
Creating staging, intermediate, and final models
Understanding and using dbt macros and Jinja templating
Managing dependencies between models
Testing and validating data quality
Documenting data models and generating dbt documentation
Using version control (Git) with dbt projects
Deploying dbt models to cloud data warehouses
Optimizing performance and maintainability of data pipelines

Benefits of Taking dbt Course

Build clean, reliable, and reusable data models
Improve SQL and data transformation skills
Ensure data quality with testing and validation
Streamline collaboration using version control (Git)
Enhance understanding of modern data warehousing workflows
Document and maintain data pipelines efficiently
Prepare data for analytics, BI, and data science projects
Boost career opportunities in data engineering and analytics roles

Career Opportunities After Completing dbt Training

Analytics Engineer
Data Engineer
BI Developer / BI Analyst
Data Analyst
Data Scientist
ETL/ELT Specialist
Cloud Data Platform Specialist

Key Features

100% Job Assistance
1 On 1 Training Option Available
24 X 7 Lifetime Support & Access
Small Batches Upto 10 Participants
Experienced & Professional Trainers
Flexible Schedule

Course Curriculum

Lesson 1 - Introduction to dbt & Modern Data Workflows

1. What is dbt and why use it

2. dbt in the modern data stack

3. dbt Core vs dbt Cloud

4. Connecting dbt to a data warehouse & Git repo

Lesson 2 - dbt Project Setup

1. Installing dbt and environment setup

2. Initializing a dbt project

3. dbt project structure (folders, configs)

4. Profiles and connection configuration

Lesson 3 - dbt Models

1. Creating dbt models (SELECT statements)

2. Using ref() for dependencies

3. Staging / intermediate / mart layer best practices

4. Model configurations

Lesson 4 - Materializations

1. What are materializations

2. Table, view, incremental, ephemeral

3. Choosing correct materialization strategies

Lesson 5 - Sources & Seeds

1. Defining sources

2. Source freshness checks

3. Using seed files for static/reference data

Lesson 6 - dbt Testing

1. Built‑in dbt tests (unique, not null, relationships)

2. Custom tests

3. Applying tests in workflows

Lesson 7 - Documentation & Lineage

1. Writing doc blocks and metadata

2. Generating dbt Docs site

3. Viewing model lineage & descriptions

Lesson 8 - Jinja Templating & Macros

1. Introduction to Jinja

2. Writing reusable macros

3. Dynamic SQL with templates

Lesson 9 - Snapshots

1. What snapshots are

2. Implementing historical data capture

3. Snapshot configuration best practices

Lesson 10 - Packages & Extensions

1. Using community packages

2. Extending dbt with plugins

Lesson 11 - Deployment, CI/CD & Orchestration

1. Scheduling dbt runs

2. Git workflows (branches, pull requests)

3. Automating dbt jobs in production

Lesson 12 - Debugging & Best Practices

1. Debugging model errors

2. Project best practices (naming, refactoring)

3. Version control strategies

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Course Fees

Online Class Room Program

US $ 799.00

100% Money Back Guarantee

Duration : 40 Hrs
Plus Self Paced

Classes Starting From

Fast Track Batch 07 Jul 2026
Weekday Batch 13 Jul 2026
Weekend Batch 11 Jul 2026

Corporate Training

Customized Training Delivery Model
Flexible Training Schedule Options
Industry Experienced Trainers
24x7 Support

Trusted By Top Companies Worldwide

Want to know Today's Offer

DBT Certification Exam

Latest Official Certifications Name:

dbt Analytics Engineering Certification: shows core analytics engineering expertise.

dbt Cloud Architect Certification: demonstrates advanced dbt Cloud architectural skills.

Exam Format (Both Certifications):

Number of Questions: 65 questions
Duration: 2 hours (120 minutes)
Passing Score: 65% or higher
Delivery: Online proctored exam (you schedule a time and take it remotely)
Validity: 2 years
Price: Around $200 USD per attempt
Language: English (with additional language options available for some exams)

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DBT (Data Build Tool) Training Course