Solutions
Businesses need to store and analyze data efficiently. Using Snowflake, organizations have the ability to scale their data warehouse up and down as the situation demands. Its unique shared data architecture allows for easy scalability. Snowflake's fully relational SQL data warehouse is built for the cloud, making it effecient to store and access all your data from one integrated location. Instead of separating production and analysis databases, Snowflake uses virtual data warehouses to allow unlimited access and computational power, delivering on performance, simplicity, and affordability.
Until recently, advancements in data warehousing and analytics were largely incremental. Small innovations in database design would herald a new data warehouse every 2-3 years, which would then quickly become overwhelmed with ever-increasing data volume. Read how Snowflake and Tableau together are revolutionizing the speed of analytics.
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Snowflake's multi-cluster, shared data architecture was built for the cloud from the beginning. Data is stored in Amazon S3 and is accessible independently from as many virtual data warehouses as you need. Because computing and storage are completely separate, you can independently scale either to meet your needs at any time.
Learn moreTableau is the friendliest way for our business to explore data. When you're lost in a sea of data, a visualization can act as a sort of information map. When combined with Snowflake's speed, we can now explore this information map at the speed of thought and move from data to information to a decision 10 times faster.
Due to growing data, The University of Notre Dame’s fundraising office adopted the Snowflake Elastic Data Warehouse. With Snowflake’s virtual data warehouses, the office instantly matched capacity with need—in many cases, their analysis came 10x faster. Using Tableau, Notre Dame takes advantage of that speed with direct connectivity for both dashboard creation and sharing. With Tableau and Snowflake, the University of Notre Dame has a platform that is scalable, fast, and accessible.
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With a scalable AWS back-end, support for virtual warehouses, and the capability to work with structured and semi-structured data, Snowflake has the flexibility to adjust to demanding workloads.
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