DBT: Data Build Tool Overview
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Top Section (What is DBT?)
- Icon: Database with arrows representing data transformation.
- Text: "DBT (Data Build Tool) is an open-source tool for transforming data within data warehouses. It simplifies the ELT (Extract, Load, Transform) process, using SQL for modeling data."
Middle Section (Advantages & Disadvantages):
Left Column (Advantages):
- Icon 1: Scalability (servers growing or expanding).
- Icon 2: SQL symbol (highlighting simplicity).
- Icon 3: Git logo for version control.
- Text: "Advantages: Easy to use for analysts, scalable, supports Git for version control, modular design, built-in testing and documentation."
Right Column (Disadvantages):
- Icon 1: Data warehouse icon (dependence on cloud platforms).
- Icon 2: ETL broken flowchart (missing ETL functionality).
- Icon 3: Python coding icon (limited complexity).
- Text: "Disadvantages: Requires data already in the warehouse, lacks native ETL support, limited for complex transformations."
Bottom Section (DBT vs Other Tools):
- Comparison Table:
- Columns for DBT, Airflow, Talend, and Matillion.
- Rows include categories like "Transformations," "ETL Support," and "Complexity."
- Comparison Table:
Each section should have simple illustrations, a color palette with blue tones, and professional fonts for clarity and simplicity.
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