Fivetran users are typically trying to centralize data into their data warehouse for analytics purposes. The typical workflow involves coding highly customized scripts that require adjustments as the scope of their data projects expand. With Fivetran, rather than pulling in a technical resource to build out these API call scripts, users can simple enter their instance URL and API key for authentication, and Fivetran will pull all available Coupa data into the customers’ data warehouse of choice and automating checking for updated data in Coupa to replicate into the data warehouse.
By pulling Coupa data into a centralized analytics warehouse without having to manage an ETL script, customers immediately are able to combine Coupa data with other data sets for insights to power their business.
This sort of self-maintaining data pipeline increases the chance of customer data teams (and finance teams) advocating to renew Coupa to continue using reliable models running off this data.
Automated schema creation, including data type mapping.
Automated updates, checking for updated data in Coupa.
Ongoing schema management: updating data in the data warehouse based updated data detected in Coupa.
Idempotent replication to prevent data loss and maintain data integrity
Customer success story:
Snowflake’s data science team needs to automate the migration of their Coupa data to a data warehouse where they can build out financial models. They want to capture insights around purchase orders, requisitions, exchange rates, while using tagging to create a comprehensive overview of their financial performance. Using Fivetran’s Coupa connector instead of scripting out an integration themselves resulted in 5-10x time savings.