Stripe Joins the Snowflake Inc. Retail Data Cloud to Unlock the Value of Payment Data
May 18, 2022 at 09:41 pm IST
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Snowflake Inc. announced that Stripe has joined the Snowflake Data Cloud and Retail Data Cloud, to enable joint customers in any industry, including retail and consumer packaged goods, to access and leverage their Stripe payment data directly in Snowflake. Through Stripe Data Pipeline and Snowflake Secure Data Sharing, customers will be able to join all their Stripe data and reports with other operational data stored in Snowflake giving companies a single source of truth for making business decisions. As digitization and eCommerce continue to grow at a rapid pace across B2B and B2C companies, organizations are struggling to integrate and effectively analyze payment processing data alongside other data sets as they use it
for business activities like monitoring for fraud, analyzing demand, and marketing to customers. IT teams frequently need to set up a separate data pipeline to ensure that teams across the organization are able to analyze payment processing data, resulting in teams making decisions based on incorrect or outdated data. Stripe Data Pipeline makes it easy to unify data streams by sharing the up-to-date Stripe data and reports of a user directly to their Snowflake account in a few clicksno code needed. Data Pipeline takes advantage of Snowflake Secure Data Sharing, which enables organizations like ChowNow and Lime to share data across their business ecosystem without copying, transforming, and moving data. As a result, Snowflake customers can be confident that their Stripe data is up to date and accurate as they analyze it alongside marketing, supply chain, and other data sets available on Snowflake Data Marketplace to deliver exceptional, personalized customer experiences and optimize operations for business across the sector.
Snowflake Inc. enables every organization to mobilize their data with Snowflakes Data Cloud. The Companyâs platform powers the Data Cloud, enabling customers to consolidate data into a single source of truth to drive meaningful business insights, apply artificial intelligence (AI) to solve business problems, build data applications, and share data and data products. Its platform supports a range of workload, including data warehouse, data lake, data engineering, AI/machine learning (ML), applications, collaboration, cybersecurity, and Unistore. Its cloud-native architecture consists of three independently scalable but logically integrated layers across compute, storage, and cloud services. The compute layer provides dedicated resources to enable users to simultaneously access common data sets for many use cases with minimal latency. The storage layer ingests massive amounts and varieties of structured, semi-structured, and unstructured data to create a unified data record.