Omnata Push now supports Salesforce Marketing Cloud, SFMC. Push data directly from Snowflake, manage like SQL, integrate with dbt. Learn more about the approach and see it in action.
As companies have increasingly global workforces and customers, it's worth the time for Salesforce administrators to understand how multi-currency works. It doesn't involve any obscure knowledge of finance, and is probably simpler than you think.
Learn about the latest approach to Salesforce with Large Data Volumes (LDV) for 2021. Salesforce can now be directly connected to cloud data warehouses; Snowflake and BigQuery, that are designed to handle operational scale workloads. Live-queries solve a bunch of problems faced by traditional extract and load integrations. Omnata unlocks integration use cases like product data, revenue and transactional data, machine learning outputs, and patient records.
Omnata drastically simplifies integration tasks, from Snowflake to Salesforce and BigQuery to Salesforce. Previously, this required middleware with complex setup and constant maintenance. The simplicity of this new approach rests on two key components, cloud-native data warehouse design and Salesforce Connect external objects.
Your teams need a complete view of customers but that doesn’t mean you need to cram all of that data into your CRM. Previously, opening up live access to your production data warehouse was unthinkable, but BigQuery's cloud architecture is designed for concurrent queries and huge datasets. Omnata’s connector makes the most of this, returning datasets to external objects without loads or syncs.
We thought about the priorities of data teams and the existing tools that they use and concluded that outbound data integration could be further simplified. We built a data-engineer friendly experience that uses our native Salesforce app and the native capabilities of Snowflake and dbt, an increasingly popular combination.
Expert tips for Salesforce and Snowflake, plus, open-source and community contributions. Read insights about analytics, machine learning, enterprise architecture and data-engineering.
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