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dbt Analytics Engineering Certification

The dbt Analytics Engineering Certification validates expertise in using dbt (data build tool) to transform raw data in cloud data warehouses into clean, tested, and documented analytical datasets. It covers dbt project structure, SQL modeling with Jinja, testing strategies, documentation, macros, packages, and deployment with dbt Cloud and dbt Core. This credential is the definitive certification for analytics engineers working in the modern data stack.

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dbt Cert Exam Overview

Detail Information
Full Name dbt Analytics Engineering Certification
Governing Body dbt Labs
Number of Questions 65
Time Limit 120 minutes
Passing Score 65% (approx 43/65)
Exam Fee $200 USD
Category IT Certifications
C3RT App Available On iPhone, iPad, and Mac
Official Source dbt Labs official website ↗

dbt Cert Content Areas and Domains

Domain / Content Area Exam Weight
Data Modeling — Sources, Models, CTEs, Refs 27%
Materializations — Table, View, Incremental, Snapshot 12%
Testing — Generic and Singular Data Tests 8%
Documentation and Exposures 6%
Deployment — dbt Cloud Jobs and CI/CD 8%
Analytics Engineering Best Practices — Jinja, Macros, Packages, Semantic Layer 39%

Domain weights are approximate and based on the dbt Labs content outline. Always verify at the official source before your exam.

Topics Covered

  • Analytics Engineering Fundamentals — ELT vs ETL, the modern data stack, dbt's role
  • dbt Project Structure — dbt_project.yml, profiles, sources, seeds, snapshots
  • dbt Models — SQL models, materializations (table, view, incremental, ephemeral)
  • Jinja Templating in dbt — ref(), source(), config(), if/for, macros
  • dbt Testing — generic tests (not_null, unique, accepted_values, relationships), custom tests
  • dbt Documentation — model descriptions, column docs, dbt docs generate and serve
  • Incremental Models — is_incremental(), unique_key, merge strategies, late-arriving data
  • dbt Cloud Deployment — jobs, environments, CI/CD integration, dbt Cloud IDE

How C3RT Helps You Pass the dbt Cert

01

Adaptive Practice

Questions adapt to your weak areas automatically so every study session on the dbt Cert is time well spent.

02

Diagnostic Mocks

Full-length mock exams timed to the real dbt Cert format with detailed score breakdowns by topic.

03

Mistake Bank

Every wrong answer is saved for targeted re-drill. The system resurfaces your mistakes until they stick.

04

Native on iOS & Mac

Built with SwiftUI, not a web wrapper. Instant load, offline support, hardware-speed rendering.

dbt Cert Frequently Asked Questions

What does dbt Cert stand for?

dbt Cert stands for dbt Analytics Engineering Certification. It is administered by dbt Labs.

Who administers the dbt Cert?

The dbt Analytics Engineering Certification (dbt Cert) is administered by dbt Labs. For official information, visit the dbt Labs website.

How many questions is the dbt Cert?

The dbt Cert consists of 65 questions. Candidates are given 120 minutes to complete the exam.

What is the passing score for the dbt Cert?

The passing score for the dbt Cert is 65% (approx 43/65), as set by dbt Labs. Scoring methodology and passing standards may be updated periodically. Always verify current requirements with the governing body.

How much does the dbt Cert exam cost?

The dbt Cert exam fee is $200 USD. This fee is set by dbt Labs and may vary by testing centre, region, or membership status. Additional fees for registration or rescheduling may apply.

What is dbt and what does an analytics engineer do?

dbt (data build tool) enables analytics engineers to transform raw source data (from a data warehouse like Snowflake, BigQuery, or Databricks) into clean, reliable analytical models using SQL. Analytics engineers sit between data engineers (who load data) and data analysts (who analyze it), building the tested and documented data models that analysts rely on.

What is the ref() function and why is it important?

ref() is dbt's core function for referencing other models in your project — SELECT * FROM {{ ref('stg_orders') }} instead of hardcoding schema names. ref() handles dependency resolution (dbt builds in the correct order), enables consistent schema naming across environments (dev vs prod), and allows dbt to build the DAG of your data pipeline.

What is an incremental model in dbt?

An incremental model only processes new or changed records rather than rebuilding the entire table on each run. Using the is_incremental() macro and a unique_key, dbt generates MERGE or INSERT SQL to update only the changed records. This is critical for large tables where full rebuilds would be prohibitively expensive. The exam tests when incremental models are appropriate and how to handle late-arriving data.

How does dbt handle testing?

dbt has two types of tests: generic tests (not_null, unique, accepted_values, relationships) defined in YAML schema files, and singular tests (custom SQL queries that return failing rows). Tests are run with dbt test and can be applied to models, sources, and seeds. The exam tests how to configure tests in schema.yml files and how to write custom test macros.

C3RT is a native iOS and macOS exam preparation platform covering the dbt Analytics Engineering Certification (dbt Cert), a IT Certifications certification, administered by dbt Labs. C3RT is not affiliated with or endorsed by dbt Labs. Certification names and trademarks are the property of their respective organisations. For official exam registration, eligibility requirements, and content outlines, visit the dbt Labs official website ↗ .