4 minute read
Key Takeaways
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Snowflake Openflow and dbt Projects enable data engineers to connect to any data source and target, providing unmatched flexibility and customization for effective data management. This change allows organizations to harness diverse data sets efficiently.
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The ability to deploy and execute data pipelines within a Virtual Private Cloud (VPC) or via Snowpark Container Services simplifies the process while giving users control over their data operations. This is crucial for businesses prioritizing security and operational simplicity.
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With built-in AI capabilities for parsing and chunking unstructured data, Snowflake helps organizations bridge the gap from pipeline building to deployment, ensuring that data is prepared for AI applications. This advancement directly impacts data engineers and organizations looking to leverage AI-ready data effectively.
Join Snowflake’s Amanda Kelly, Director of Product, to learn how data engineers can use Snowflake Openflow and dbt Projects to:
- Connect to any data source and any target with the flexibility to customize and extend
- Deploy and execute pipelines inside a VPC or via Snowpark Container Services with both control and simplicity
- Bridge the gap from pipeline building to deployment natively in Snowflake
- Tackle AI-ready data using unstructured data connector with AI-enabled parsing and chunking built into the ETL pipelines
Learn More Here! Snowflake AI Data Cloud
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