Dbt (data Build Tool) For Data Transformations Training Course: Reliable Data Models

Introduction

Elevate your data transformation capabilities with our dbt (Data Build Tool) for Data Transformations Training Course. This program is designed to equip you with the essential skills to use dbt for efficient and reliable data transformations, enabling you to build robust and maintainable data models. In today's data-driven world, mastering dbt is crucial for organizations seeking to streamline their data pipelines and ensure data quality. Our dbt training course offers hands-on experience and expert guidance, empowering you to leverage dbt's capabilities for diverse data transformation tasks.

This reliable data models training delves into the core concepts of dbt, covering topics such as data modeling, testing, and documentation. You'll gain expertise in using industry-standard techniques to use dbt for efficient and reliable data transformations, meeting the demands of modern data-intensive organizations. Whether you're a data engineer, data analyst, or data scientist, this dbt (Data Build Tool) for Data Transformations course will empower you to design and implement high-quality data models.

Target Audience:

• Data Engineers
• Data Analysts
• Data Scientists
• Business Intelligence Developers
• Database Administrators
• Analytics Engineers
• Anyone needing dbt skills

Course Objectives:

• Understand the fundamentals of dbt (Data Build Tool) for data transformations.
• Master dbt project setup and configuration.
• Utilize dbt models for data transformation and modeling.
• Implement dbt tests for data quality assurance.
• Design and build efficient data pipelines with dbt.
• Optimize dbt models for performance and maintainability.
• Troubleshoot and address common issues in dbt projects.
• Implement dbt documentation for data lineage and transparency.
• Integrate dbt with various data warehouses and platforms.
• Understand how to handle incremental data transformations with dbt.
• Explore advanced dbt features (e.g., macros, packages).
• Apply real world use cases for dbt in data transformation workflows.
• Leverage dbt's ecosystem for efficient data modeling.

Duration

10 Days

Course content

Module 1: Introduction to dbt (Data Build Tool)

• Fundamentals of dbt (Data Build Tool) for data transformations.
• Overview of dbt models, tests, and documentation.
• Setting up a dbt development environment.
• Introduction to dbt project structure and configuration.
• Best practices for dbt.

Module 2: dbt Project Setup and Configuration

• Mastering dbt project setup and configuration.
• Utilizing dbt profiles and project files.
• Designing and building dbt project structures.
• Optimizing project configuration for specific data warehouses.
• Best practices for dbt project setup.

Module 3: dbt Models for Data Transformation

• Utilizing dbt models for data transformation and modeling.
• Implementing SQL-based data transformations.
• Designing and building data models with dbt.
• Optimizing models for performance and readability.
• Best practices for dbt models.

Module 4: dbt Tests for Data Quality

• Implementing dbt tests for data quality assurance.
• Utilizing built-in dbt tests and custom tests.
• Designing and building data quality tests.
• Optimizing tests for data integrity.
• Best practices for dbt tests.

Module 5: Efficient Data Pipelines with dbt

• Designing and building efficient data pipelines with dbt.
• Utilizing dbt run and build commands.
• Implementing data pipeline orchestration with dbt.
• Optimizing pipelines for specific data transformation tasks.
• Best practices for dbt pipelines.

Module 6: dbt Model Optimization

• Optimizing dbt models for performance and maintainability.
• Utilizing dbt materializations and incremental models.
• Implementing data partitioning and indexing.
• Designing scalable dbt models.
• Best practices for model optimization.

Module 7: Troubleshooting dbt Projects

• Debugging common issues in dbt projects.
• Analyzing dbt logs and error messages.
• Utilizing troubleshooting techniques for problem resolution.
• Resolving common dbt errors.
• Best practices for troubleshooting.

Module 8: dbt Documentation

• Implementing dbt documentation for data lineage and transparency.
• Utilizing dbt documentation generation.
• Designing and building data lineage diagrams.
• Optimizing documentation for data discovery.
• Best practices for dbt documentation.

Module 9: dbt Integration with Data Warehouses

• Integrating dbt with various data warehouses and platforms.
• Utilizing dbt adapters for different data warehouses.
• Implementing data integration with external data sources.
• Optimizing integration for data retrieval and processing.
• Best practices for dbt integration.

Module 10: Incremental Data Transformations

• Understanding how to handle incremental data transformations with dbt.
• Utilizing dbt incremental models for data updates.
• Implementing incremental data loading strategies.
• Designing efficient incremental data pipelines.
• Best practices for incremental models.

Module 11: Advanced dbt Features

• Exploring advanced dbt features (macros, packages).
• Utilizing dbt macros for reusable code.
• Implementing dbt packages for community-driven solutions.
• Designing and building advanced dbt projects.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced features.

Module 12: Real-World Use Cases

• Implementing dbt for data warehousing and business intelligence.
• Utilizing dbt for data transformation and modeling in analytics.
• Implementing dbt for data quality management and testing.
• Utilizing dbt for data pipeline automation.
• Best practices for real-world applications.

Module 13: dbt Tools Implementation

• Utilizing dbt tools and frameworks (dbt Cloud, dbt Core).
• Implementing dbt projects with specific tools.
• Designing and building automated deployment workflows.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: dbt Project Monitoring

• Implementing dbt project monitoring.
• Utilizing dbt logs and metrics.
• Designing and building monitoring dashboards.
• Optimizing monitoring for real-time insights.
• Best practices for monitoring.

Module 15: Future Trends in dbt Transformations

• Emerging trends in dbt for data transformations.
• Utilizing dbt with cloud-native data platforms.
• Implementing dbt for data mesh architectures.
• Best practices for future applications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.