Built a project with dbt including modeling, sources, testing, documentation, and deployment
DBT is a command-line tool that helps data analysts and engineers develop and manage the SQL code that transforms data in their data warehouses. Fundamentals of dbt typically include topics such as data modeling, working with data sources, testing, documentation, and deployment. These activities are important for building and maintaining a robust and scalable data warehouse using Snowflake.
Developed the Fundamentals of dbt including modeling, sources, testing, documentation, and deployment.
The dashboard is designed to display key insights about user behavior related to booking a ride. It aggregates, cleanses, and combines data from multiple sources to provide a comprehensive analysis. Interactive filters and visualizations are included to help stakeholders gather insights.
mlskeleton, the open-source python package, can help you create a professional and organized folder structure for your machine learning projects and streamline your workflow.
