Load data from Sprinklr to Treasure Data in a few clicks
Focus on your business, not on getting your Sprinklr data into Treasure Data. Build scalable, production-ready data pipelines and workflows in hours, not days.
Sprinklr to Treasure Data Data Pipelines Made Easy
Your unified solution for building data pipelines and orchestrating workflows at scale.
Sprinklr & 190+ Other Data Connectors, Fully Managed For You
Connect easily to Sprinklr with 100% compatibility, regular API updates, and a wide range of other pre-built data connectors out of the box.
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Start analyzing your Sprinklr data in minutes with Rivery
Sprinklr is a provider of enterprise software for customer experience management. Its software aims to help brands understand the conversations that matter most on channels such as social media, messaging, blogs, and review sites.
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