Course Description
This course introduces students to DBT (Data Build Tool), a powerful open-source tool for transforming data in the cloud. Focused on enabling scalable and maintainable data pipelines, the course covers DBT fundamentals, including writing modular SQL transformations, managing dependencies, testing data quality, and deploying models efficiently
Why should I join?
Dbt (data build tool) course is a smart move if you’re working with data in any form — especially in modern data engineering, analytics engineering, or business intelligence.
dbt is a core component of the modern data stack alongside tools like Snowflake, BigQuery, Redshift, and Looker.It’s widely used in tech companies for data transformation, modeling, and analytics engineering. dbt integrates seamlessly with:
Cloud data warehouses: Snowflake, BigQuery, Redshift.Orchestration tools: Airflow, DagsterBI tools: Looker, Metabase, Mode Learning dbt makes you more effective across the data pipeline
Please contact us if you have any questions relating to any of the vika technologies features.
Course Content
Oracle Introduction
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4 Topics
What is dbt and why is it used?
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dbt vs traditional ETL tools
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Analytics engineering and the modern data stack
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dbt Core vs dbt Cloud
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Unix Commands
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4 Topics
Installing dbt (Core or Cloud)
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Creating a new dbt project
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Connecting dbt to a data warehouse (e.g. Snowflake, BigQuery, Redshift)
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Understanding the dbt project folder structure
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OS information
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5 Topics
Creating .sql model files
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Using SELECT statements as model definitions
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Materializations: view, table, incremental, ephemeral
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Model naming conventions and best practices
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Using ref() to manage dependencies
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Copy and move commands using cp, mv command
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4 Topics
Introduction to Jinja templating
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Using variables and control flow in SQL
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Creating reusable SQL with macros
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Environment-specific logic (dev vs prod)
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Compression and un-compression
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4 Topics
Built-in tests: unique, not null, accepted_values, relationships
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Writing custom tests
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Test naming and structure
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Running and interpreting tests
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Changing file permission
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4 Topics
Writing model and column-level docs with YAML
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Auto-generating documentation with dbt docs generate
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Visualizing DAGs (lineage graphs)
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Hosting and sharing documentation
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Scheduling the job
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3 Topics
Defining and using sources (external/raw tables)
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Using seeds to load small static CSVs
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Version-controlling seed data
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Editor command
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4 Topics
What are snapshots?
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Slowly Changing Dimensions (SCD Type 2)
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Setting up and scheduling snapshots
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Snapshot configuration and testing
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Best Practices and Advanced Concepts
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5 Topics
Using packages from dbt Hub
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Advanced Jinja usage
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Cross-database models (multi-warehouse)
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Handling incremental models efficiently
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Modularizing logic with macros and hooks
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Final Project Ideas
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4 Topics
Overview of dbt Cloud workflows
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Creating jobs and scheduling runs
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Notifications and monitoring
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Using dbt with CI/CD (GitHub Actions, GitLab CI)
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Integration with Other Tools
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3 Topics
Orchestrating with Airflow, Prefect, Dagster
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Working with BI tools (e.g. Looker, Mode)
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dbt + Snowflake/BigQuery best practices
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Capstone Project
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1 Topic
Build a real-world dbt pipeline:
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Includes
12 Lessons
45 Topics
Admin
