Global hooks in Mage are a powerful feature that allow executing custom code before or after API operations. They provide flexibility to extend functionality, integrate with external systems, validate data, and more across different components of your application. With targeting conditions and asynchronous execution, global hooks offer granular control and performance optimization.

In this tutorial, we integrate dbt with Mage to create a data pipeline, moving data from a source to a PostgreSQL database and performing SQL transformations through staged models. By setting up Docker and PostgreSQL, and following a step-by-step process, we effectively manage data orchestration and analytics using Mage and dbt.

Backfilling integrates historical data into data pipelines, ensuring completeness and mitigating failures. Mage provides a no-code UI and custom coding options to streamline backfilling for robust, resilient data pipelines.

What are people saying about Mage, the modern day open-source data pipeline tool for transforming and integrating your data? Discover the buzz for yourself by checking out these blogs and articles written by those in the data engineering community!

Mage now supports a suite of DuckDB & MotherDuck features— from reading and writing DuckDB databases to executing dbt with dbt-duckdb!

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This article outlines the integration between Mage and Google BigQuery, a serverless data warehousing service. We'll discuss the integration process, its benefits, and how it aids businesses in making data-driven decisions.

Google BigQuery is a serverless, scalable data warehouse on Google Cloud. It supports real-time analytics, machine learning, and GIS capabilities. With its unique architecture separating storage and computing, it offers automatic scalability and strong security, ideal for data-driven businesses.

Snowflake is a cloud-based data warehousing platform that brings a new level of performance, simplicity, and affordability to businesses that require big data processing and analytics.