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Building an Amazon Web Services Data Warehouse with Snowflake

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In the age of Big Data, the modern enterprise needs to collect, store, and analyze increasing amounts of data in order to monitor critical business functions,
properly allocate monetary and human capital resources, and make informed strategic business decisions.

In order to process, transform, and share data across business units, subsidiaries and partners with often hundreds to thousands of concurrent users, enterprises have turned to Cloud computing and data services such as Amazon Web Services (AWS) and SaaS-based data warehousing to store data efficiently, minimize cost
and human capital output, and deliver business insights in real-time.

An Amazon WeB Services Data Warehouse
Built for Your Needs

An Amazon Web Services data warehouse needs to combine the access, scale, and OpEx cost flexibility of Cloud computing services with the analytics power of an elastic, SaaS data warehouse to rapidly extract and share key data insights anytime, anywhere.

Snowflake on AWS delivers this powerful combination with a SaaS-built SQL data warehouse that handles diverse data sets in a single, native system. Snowflake automatically scales workload, data, and user demands to provide full elasticity – businesses only pay for what they need

Amazon Web Services data warehouse

The Power of Snowflake on Amazon Web Services

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Snowflake: An AWS Partner for the Cloud Data Warehouse 

As an Amazon Web Services partner, Snowflake offers a full range of support for AWS-supported data warehousing, including:

  • Support for AWS PrivateLink to allow Snowflake customers to easily and securely connect to their Snowflake instance without the need to access the public Internet
  • Snowflake Snowpipe to give Snowflake customers an automated, cost-effective service to load data from AWS into Snowflake. Built with Amazon SQS and other AWS solutions, the service asynchronously detects and loads new data into Snowflake from Amazon Simple Storage Service (Amazon S3)
  • Easy integration with AWS Glue to flexibly manage data transformation and ingestion pipelines.
  • Snowflake data access for AWS Sagemaker to speed data prep times and create a single source of truth for Amazon’s new machine learning modeling services.

AWS Businesses: Start Improving Outcomes and Reducing Risk

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