Top Data Build Tool Training – DBT Training in Hyderabad

1. Modern Data Transformation in the Analytics Stack How DBT Differs from Traditional ETL Tools www.visualpath.in

2. The Traditional ETL Model Title:Traditional ETL: Extract → Transform → Load • Data is extracted from source systems • Transformed using an external ETL engine • Loaded into a data warehouse • Common tools: Informatica, Talend, SSIS, DataStageChallenges: • Complex to manage and maintain • Slow iteration cycles • Limited transparency into transformations www.visualpath.in

3. Enter DBT – The Modern Way Title:dbt: Transform After Load (ELT) • ELT process: Extract and load data first, then transform • dbt focuses solely on the transformation layer • Leverages the compute power of modern data warehouses • Uses SQL and Jinja for modular, testable models • Embraces version control and CI/CD workflows www.visualpath.in

4. Title:Traditional ETL vs. dbt ELT Architecture Key Architectural Difference www.visualpath.in

5. Developer Experience Title:Built for Analysts and Engineers • Traditional ETL tools often require complex scripting or proprietary GUIs • dbt enables analytics engineers to write transformations using SQL • Modular and reusable logic with clear dependencies • Easy to test, debug, and document • Encourages fast development cycles and collaboration www.visualpath.in

6. Collaboration & Governance Title:Software Engineering Best Practices in dbt • Version-controlled codebase using Git • Automated documentation of models and lineage • Built-in data quality tests for confidence in outputs • Supports peer review and CI/CD pipelines • Brings discipline and accountability to data transformation www.visualpath.in

7. Performance & Scale Title:Leverages the Power of Cloud Data Warehouses • dbt compiles SQL and runs transformations directly in platforms like Snowflake, Big Query, and Redshift • No need for a separate compute engine • Scales with your warehouse’s performance • Simplified architecture with fewer moving parts www.visualpath.in

8. Title:Choosing Between dbt and Traditional ETL When to Use What? www.visualpath.in

9. Summary & Takeaways Title:dbt vs. ETL: A Paradigm Shift in Data Transformation • dbt focuses on transformation after data is loaded • Encourages clean, testable, version-controlled SQL-based pipelines • Promotes better collaboration between data engineers and analysts • Ideal for modern data stacks leveraging cloud warehouses • Not a full ETL tool — but the gold standard for in-warehouse transformation. www.visualpath.in

10. For More Information About DBT (Data Build Tool) Address:- Flat no: 205, 2nd Floor, Nilagiri Block, Aditya Enclave, Ameerpet, Hyderabad-16 Ph. No: +91-998997107 Visit: www.visualpath.in E-Mail: online@visualpath.in www.visualpath.in

11. Thank You • Visit: www.visualpath.in www.visualpath.in