dbt Articles

101 articles on dbt certification prep and technical concepts

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dbt

101 articles

dbt Models: SQL-Defined Transformation Units (2026)

Model fundamentals — SELECT-based definitions, naming, refs, config blocks. The atomic unit of every dbt project.

dbt Analytics Engineering Exam: Complete Guide (2026)

Pass the AE Certification — scope, weighting, sample questions, and a focused study plan. The dbt cert that anchors AE work.

dbt Cloud vs dbt Core: Feature & Cost Comparison (2026)

Honest comparison of dbt Cloud vs. dbt Core — IDE, scheduler, semantic layer, security. When the Cloud upgrade pays for itself.

dbt Project Structure: models/seeds/macros Layout (2026)

dbt_project.yml Explained: Every Config (2026)

Every dbt_project.yml setting that matters — paths, vars, materializations, hooks. The control center of your project.

profiles.yml: Connection & Target Configuration (2026)

profiles.yml structure — adapters, targets, env vars, secrets. Local vs. CI/CD setup patterns.

dbt Sources: External Tables & Freshness Checks (2026)

Source definitions, freshness, source freshness reports. Track upstream data without owning the ingestion.

dbt Seeds: Loading CSVs into the Warehouse (2026)

Seed mechanics — CSV ingestion, types, refresh strategy. Where seeds fit and where they don't.

dbt Snapshots: SCD Type 2 in SQL (2026)

Snapshot strategies — timestamp, check, dbt_valid_from/to columns. The native way to track slowly changing dimensions.

dbt Exposures: Document Downstream Consumers (2026)

Exposures for dashboards, ML models, applications. Make downstream usage visible in your DAG.

dbt Tests: Generic, Singular, Source Freshness (2026)

Every test type in dbt — generic, singular, source freshness, custom. The data-quality backbone of dbt.

dbt Analyses: Reusable Ad-Hoc Queries (2026)

Analyses directory — compiled-but-not-run SQL for ad-hoc reporting. When to reach for analyses.

dbt Macros: Reusable Jinja-SQL Logic (2026)

Macro fundamentals — definitions, arguments, namespacing, common reuse patterns. The DRY layer of dbt.

dbt Packages: Dependency Management (2026)

packages.yml structure, common community packages, version pinning. Lean on dbt_utils, dbt_expectations, audit_helper.

dbt Hooks: pre-hook, post-hook, on-run (2026)

Hook types — model-level, project-level, run-level. Common use cases like GRANTs, audit, and refresh triggers.

dbt Operations: Run Macros via run-operation (2026)

Operations for ad-hoc macro execution — common patterns like permissions, vacuum, custom maintenance.

dbt Artifacts: manifest, run_results, sources, catalog (2026)

The four dbt artifacts — what's in each, when they're written, how to consume them programmatically.

dbt manifest.json: Project Graph Reference (2026)

manifest.json schema — nodes, sources, exposures, lineage. The data behind every dbt graph operation.

dbt run_results.json: Execution Telemetry (2026)

run_results.json schema — node status, timing, messages. Where to look after dbt run/test/build.

dbt catalog.json: Generated by dbt docs (2026)

catalog.json structure — column-level metadata from the warehouse. Generation cost and refresh strategy.

dbt Graph Context: graph object inside Jinja (2026)

graph context object — access nodes, sources, metrics from Jinja. The advanced metaprogramming layer of dbt.

dbt CLI Commands: run / test / build / compile (2026)

Every dbt command compared — run, test, build, compile, snapshot, source freshness. Selection criteria for each.

dbt compile: Generating SQL Without Executing (2026)

What dbt compile produces — target/compiled, target/run, manifest. Patterns for inspection and CI/CD.

dbt build: Combined run + test + snapshot + seed (2026)

Why dbt build is usually the right command — DAG ordering, fail-fast on test failures, deferral.

dbt run vs dbt build: Choosing the Right Command (2026)

When dbt run beats dbt build (and vice versa). Common scenarios and CI/CD recommendations.

dbt Node Selection: select, exclude, methods (2026)

Selection syntax — tag, source, exposure, state. Build runtime subsets with precision.

dbt state and defer: Slim CI Foundation (2026)

state:modified+, defer, and how they enable Slim CI. The patterns every CI pipeline needs.

dbt Materializations: view, table, incremental, ephemeral (2026)

Every materialization type — semantics, when each fits, cost trade-offs. The most-tested dbt concept.

View Materialization: Default and Cheap (2026)

When views beat tables — query frequency, source freshness, warehouse compute. The right default for many models.

Table Materialization: Full Refresh Patterns (2026)

Table materialization mechanics — drop and recreate, swap, performance characteristics on each warehouse.

Incremental Materialization: Smart Updates (2026)

Incremental fundamentals — is_incremental(), unique keys, on schema change. The right way to scale dbt models.

Ephemeral Materialization: Inline CTEs (2026)

Ephemeral mechanics — inlined CTEs, restrictions, when CTE explosion hurts performance.

Materialized View Materialization: Warehouse-Native (2026)

When dbt-managed materialized views pay off — adapter support, refresh modes, common gotchas.

dbt Incremental Strategies: merge / delete+insert / append / insert_overwrite (2026)

Every incremental strategy compared — semantics, adapter support, performance trade-offs.

Incremental merge Strategy: Upsert Pattern (2026)

merge strategy mechanics — unique_key requirement, performance on each warehouse, the most common choice.

Incremental append Strategy: Pure Insert (2026)

append strategy — no merge, fastest path. When to use and how to prevent duplicates.

Incremental delete+insert Strategy (2026)

delete+insert mechanics — when it beats merge, partition pruning, warehouse-specific behavior.

Incremental insert_overwrite: Partition Replacement (2026)

insert_overwrite for partition-based replacement — BigQuery/Databricks support, incremental_predicates usage.

Incremental unique_key: Composite Keys & NULLs (2026)

unique_key semantics — single vs. composite, NULL handling, common deduplication issues.

incremental_predicates: Filtering the Merge Target (2026)

incremental_predicates for performance — limiting merge scan, partition pruning, common patterns.

on_schema_change: Handle Column Drift (2026)

on_schema_change options — ignore, append_new_columns, fail, sync_all_columns. When each is safe.

Custom Materializations: Going Beyond Built-Ins (2026)

Custom materializations in macros — config wrapper, before-begin hooks, common community examples.

Generic Tests: Schema-Driven Data Quality (2026)

Generic tests — declared in yml, reusable. The first line of defense for data quality.

dbt unique Test: Detect Duplicate Keys (2026)

How unique works — query pattern, warehouse cost, severity, store_failures.

dbt not_null Test: Catch Missing Values (2026)

not_null mechanics, where to apply, how to handle expected NULLs without disabling the test.

dbt accepted_values: Enum Validation (2026)

accepted_values usage — quoting, source-of-truth maintenance, integration with dbt_utils.

dbt relationships Test: Referential Integrity (2026)

relationships test — referenced field validation, common false positives, warehouse cost.

Custom Singular Tests: One-Off SQL Assertions (2026)

Singular tests for project-specific data quality. Patterns for warnings vs. failures.

Custom Generic Tests: Parameterized Reuse (2026)

How to write your own generic tests — naming, arguments, severity. Patterns for team-wide test libraries.

dbt Data Contracts: Enforced Column Schemas (2026)

Data contracts mechanics — type enforcement, constraint declaration, supported adapters.

dbt Constraints: NOT NULL, UNIQUE, PRIMARY KEY (2026)

Constraint declaration in yml — warehouse support, enforcement modes, common patterns.

dbt_expectations Package: Great Expectations–Style Tests (2026)

dbt_expectations test library — value distributions, ranges, schema. Patterns for advanced data quality.

Jinja Basics for dbt: Syntax You Need (2026)

Jinja syntax for dbt — expressions, statements, filters, whitespace control. The essential subset.

dbt ref() Function: Dependency Resolution (2026)

How ref() builds the DAG, package-scoped references, version-aware lookups. The most-used dbt function.

dbt source() Function: Upstream Table Reference (2026)

source() usage — selecting from sources, freshness, override patterns. The bridge to non-dbt data.

dbt config() Function: Inline Model Configuration (2026)

config() inline syntax — materialization, tags, vars. When inline beats yml-based config.

dbt var() Function: Project Variables (2026)

var() lookup — defaults, project-level, CLI overrides. The right way to parameterize runs.

dbt env_var() Function: Secrets & Environment (2026)

env_var() patterns — required vs. default, secrets in CI/CD, common pitfalls with caching.

dbt this Function: Self-Reference for Incremental Models (2026)

this object — current relation in incremental logic, common is_incremental() patterns.

dbt_utils Package: Essential Utility Macros (2026)

Most-used dbt_utils macros — surrogate_key, star, deduplicate, date_spine, pivot.

dbt audit_helper Package: Diff Models for CI (2026)

audit_helper for table comparison — row counts, column distributions, value diffs. CI safety net.

Macro Dispatch: Adapter-Specific Implementations (2026)

Dispatch pattern for cross-adapter packages — namespaces, fallback macros, common community use.

dbt Semantic Layer: MetricFlow Foundations (2026)

The dbt Semantic Layer — semantic models, metrics, queries. Why a metric layer matters for BI.

MetricFlow: The dbt Metrics Engine (2026)

MetricFlow architecture — query compilation, dimension resolution, supported integrations.

dbt Metrics: Aggregation, Ratio, Cumulative (2026)

Metric types in the semantic layer — definitions, expressions, time-grain handling.

dbt Dimensions: Time and Categorical (2026)

Dimension declaration — categorical, time, entity. The slicing axis for every metric query.

dbt Measures: Numeric Building Blocks for Metrics (2026)

Measure declaration — aggregation type, expr, non_additive_dimension. The foundation of every metric.

dbt Model Versions: Breaking-Change Management (2026)

Versioned models — defined_in, version selectors, deprecation. Manage breaking changes safely.

dbt Model Access: private, protected, public (2026)

Access modifiers — boundary rules across projects, governance patterns at scale.

dbt Model Groups: Bundle Models for Governance (2026)

Groups for ownership, access boundaries, exposure scope. Patterns for multi-team projects.

dbt Model Contracts: Schema-Enforced Outputs (2026)

Model contracts — enforced columns, types, constraints. Stops breaking changes at build time.

dbt Mesh & Governance: Cross-Project Coordination (2026)

dbt Mesh foundations — versioned models, access, groups, contracts. The pattern for many-team analytics.

dbt-snowflake Adapter: Configuration & Tips (2026)

Snowflake adapter specifics — connection, warehouse routing, transient tables, common gotchas.

dbt-bigquery Adapter: Slot Management & Partitioning (2026)

BigQuery adapter — partitioning, clustering, dataset locations, performance characteristics.

dbt-redshift Adapter: VACUUM, DIST, SORT (2026)

Redshift adapter specifics — distribution keys, sort keys, vacuum and analyze patterns.

dbt-databricks Adapter: Liquid Clustering & Delta (2026)

Databricks adapter — Delta materializations, Unity Catalog, Liquid Clustering integration.

dbt-postgres Adapter: Local Dev Setup (2026)

Postgres adapter for local dev — install, role setup, common gotchas. The default starter adapter.

dbt-duckdb Adapter: Embedded Analytics with dbt (2026)

DuckDB adapter — local file workflows, S3 integration, MotherDuck patterns.

dbt Cloud Jobs: Scheduled & Triggered Runs (2026)

dbt Cloud job types — scheduled, CI, deferred. Configuration patterns that scale.

dbt CI/CD Overview: PR to Production (2026)

End-to-end dbt CI/CD — pre-commit, PR testing, prod deploys, rollback. The patterns teams actually use.

Slim CI for dbt: Test Only What Changed (2026)

Slim CI mechanics — state:modified+, defer, manifest comparison. The right way to scale dbt CI.

dbt CI Environment Variables: Common Patterns (2026)

Standard CI env vars — DBT_PROFILES_DIR, DBT_TARGET, secrets. The right scope per platform.

dbt Environments: dev / ci / prod Layout (2026)

Environment configuration patterns — targets, schemas, connection strategy. The model that survives growth.

dbt Branch Strategy: Trunk vs Feature (2026)

Branching strategies for dbt — trunk-based, GitFlow, environment branches. Trade-offs per team size.

dbt Blue-Green Deploys: Zero-Downtime Schema Swaps (2026)

Blue-green deploy patterns for dbt — clone-and-swap, parallel build, atomic rename.

dbt Production Deploy: Job Architecture (2026)

Production deploy architecture — schedule, full vs. incremental, snapshot timing. Reliability patterns.

dbt Layered Architecture: Staging/Marts (2026)

Layer design — staging, intermediate, marts. The standard project structure.

Staging, Intermediate, Marts: Layer Responsibilities (2026)

What belongs in each dbt layer — column renames, joins, business logic, presentation. Decision framework.

dbt Naming Conventions: stg_, int_, fct_, dim_ (2026)

Standard naming prefixes — sources, staging, intermediate, marts. The convention that scales.

dbt Performance Tuning: Common Wins (2026)

Performance tuning checklist — incremental scope, ref usage, warehouse routing, materialization choice.

Incremental Optimization for dbt Models (2026)

Practical incremental performance — predicates, partitioning, merge cost, late-arriving data patterns.

dbt Troubleshooting Guide: Common Errors (2026)

Common dbt errors and resolutions — compilation, deps, materialization, CI/CD pitfalls.

Analytics Engineer Career & Salary (2026)

Career value of the dbt AE certification — market demand, salary ranges, role progression. Honest 2026 data.

dbt Certifications: AE Cert Explained (2026)

Overview of dbt's Analytics Engineering certification — scope, prerequisites, and how it positions you for AE roles.

dbt AE Certification Difficulty: Honest Assessment (2026)

How hard the dbt AE cert really is — based on candidate reports, prerequisite skills, and exam style.

dbt AE Exam Cost: Fees, Vouchers, Retakes (2026)

Cost breakdown for the dbt AE exam — base fee, vouchers, retake policies, learning bundle deals.

dbt AE Exam: Test-Day Experience (2026)

First-hand AE exam accounts — proctoring, time pressure, common question styles. Calibrate your prep.

dbt Cloud Free Trial: Developer Plan for Study (2026)

Use the dbt Cloud Developer Plan for cert study — what's free, what's limited, common practice scenarios.

dbt AE Sample Questions: Format Walkthrough (2026)

Real-format dbt AE sample questions with answer reasoning. Calibrate to the exam before paid prep.

dbt AE Study Guide: 4-Week Plan (2026)

A focused 4-week study plan for the AE certification — official materials, hands-on, mock-exam strategy.

dbt AE Study Time: How Long It Really Takes (2026)

Realistic study-time estimates for the dbt AE cert by background. SQL fluency vs. dbt familiarity matter most.