Why forward-thinking organizations are turning to a data mesh architecture.

Data lakes can save your enterprise money but come with unique challenges. These tips will help you overcome three of the biggest issues.

Exploring fraud detection with automated data integration in a cloud data warehouse: part two of two.

Learn how CHS Inc., a Fortune 500 secondary cooperative, leverages Fivetran, Snowflake and dbt to improve supply chain efficiency and power its billion-dollar operation.

Why data lakes are the essential centerpiece of modern data architectures and an indispensable prerequisite for AI.

This marks an incredible three-peat win, solidifying our ongoing commitment to innovation and collaboration within the Google Cloud ecosystem.

Today’s business environment depends on collecting and analyzing a broad range of data. Data integration, therefore, has become critical when consolidating diverse data types. Without data integration, you’re left with siloed information that’s very difficult—if not impossible—to analyze. Comma-separated values play a fundamental role in data integration, especially when you need to join tables that share column names or want to move datasets between analytical tools.

From new data sources to cloud regions and destinations, Fivetran continues to expand what it means to be the leader in data movement.

The Fivetran REST API makes it a breeze to automate the deployment, configuration and management of connectors, saving you time and effort.

Fivetran and Google Cloud synergize incredibly well, bringing generative AI to your fingertips.