Mage Blog

AWS S3 is a widely used option for data lake, let’s see how Singer helps Data Engineers to sync data from AWS S3 (source) to Postgres Database (destination).

Databases aren’t the only sources of data, modern data pipelines can consume data from various sources.

We setup Hyperquery at Mage to organize and streamline our growth data for better insights. In this blog, we go over our experience of quickly adopting the tool and easily sharing our analysis with our peers.

Mage is an open-source data pipeline tool for transforming and integrating data. Find out how Mage compares to open-source ELT alternatives like Airbyte. We’ll break down the features, pricing, pros, cons, and more.

Mage is an open-source data pipeline tool for transforming and integrating data. Find out how Mage compares to ELT companies like Fivetran. We’ll break down the features, pricing, pros, cons, and more.

Data integration is synchronizing information between 1 system (e.g. Salesforce) and another (e.g Snowflake).

Accuracy tells overall correctness. Precision is specific to a category. Recall tells you successful detection of a specific category.

Clean data sets the foundation for the success model to be built. Ensuring your AI/ML models are build with clean data can save time and money.

Partitioners of machine learning (ML) find data cleaning the #1 pain point, but are the current resources available enough to solve the problem? Join our discussion as we try to find out what data scientists need.

Create accurate predictions, eliminate guesswork, and create magical customer experiences with Mage.