Building Continuous Pipelines Using Snowflake Dynamic Tables and dbt cloud

Do you work on streaming pipelines, Change Data Capture (CDC) use cases, or manage incremental updates for your pipelines? Are you building your architecture for current batch analytical needs but also future streaming use cases? We got you. 

Streaming and continuous pipelines are often difficult to work with. That’s why we built Dynamic Tables (currently in public preview). Dynamic Tables is a new table type that drastically simplifies continuous data pipelines for transforming both batch and streaming data, declaratively. Simply using SQL, you can build continuous pipelines with just a few lines of code. 

Watch this webinar to learn from Snowflake and dbt experts on:

• Bringing batch and streaming pipelines together 
• How to build continuous pipelines and incremental updates in Snowflake 
• How latency can be a single parameter change, and an “afterthought” 
• Using dbt to build pipeline workflows with Dynamic Tables