Modern warehouses change the paradigm meaning data and IT teams can stop double handling data.
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.
By the end of this article, regardless of your stack, hopefully, you’ll have an appreciation for the general challenges when taking analytics projects into production and some ideas on how to overcome them. Or at the very least, some new things to consider.
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