Load data from Snapchat Ads to Treasure Data in a few clicks
Focus on your business, not on getting your Snapchat Ads data into Treasure Data. Build scalable, production-ready data pipelines and workflows in hours, not days.
Snapchat Ads to Treasure Data Data Pipelines Made Easy
Your unified solution for building data pipelines and orchestrating workflows at scale.
Snapchat Ads & 190+ Other Data Connectors, Fully Managed For You
Connect easily to Snapchat Ads with 100% compatibility, regular API updates, and a wide range of other pre-built data connectors out of the box.
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Ask us anything. We have the best customer support in the industry, staffed with data experts who are ready to help solve your data challenges.
Start analyzing your Snapchat Ads data in minutes with Rivery
About Snapchat Ads
Companies use Snapchat Ads to generate brand awareness, increase engagement, and drive conversions. Ads are available in a number of formats, including stories, filters, AR lenses, and collection ads.
About Treasure Data
Treasure Data is an enterprise customer data platform that offers end-to-end, fully-managed cloud service for big data. The company is providing the ability to aggregate and translate massive volumes of scattered and siloed data. It helps to harness and analyze the information that needs to create a data-driven enterprise.
Rivery's SaaS platform provides a unified solution for ingestion, transformation, orchestration, and data operations.
“We saved several $100K we could have spent on development and maintenance. Within a few hours, you can build a production-ready, scalable ETL system.”
Gal Bar, Founder and CEO
“We solved some of our most complex data challenges with Rivery. The ability to create a unified data pipeline that is always up-to-date has been a game changer.”
Tali Stern, Director of Business Intelligence
“Rivery has more than delivered on the value proposition I sold my leadership on. Rather than hiring two more developers, I’ve been able to build all these pipelines on my own.”
Sean Lucas, Head of Data Engineering
"A reporting process that once required back-and-forth between different teams is now executed ad-hoc by team leads in minutes, cutting time to execution in half."
Jean Huang, Analytics Manager