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.
A very common (and very reasonable) question I hear, is "how is Omnata different to Tableau/Einstein/Fivetran/Mulesoft/Workato/etc with respect to Salesforce?" The answer depends on a few things. Operational or Analytics? Which Salesforce cloud? Which direction? In 2021, there are more options than ever so we boil them down for you.
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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