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 quickly become overwhelmed with rapidly increasing data volumes. Knowledge workers struggled to access those databases with development intensive business intelligence tools designed for reporting, rather than exploration and sharing. Both databases and business intelligence tools were strained in locally hosted environments that were inflexible to growth or change.
Snowflake and Tableau represent a fundamentally different approach. Snowflake’s multi-cluster shared data architecture was designed for the cloud and to handle logarithmically larger data volumes at blazing speed. Tableau was made to foster an interactive approach to analytics, freeing knowledge workers to use the speed of Snowflake to their greatest advantage.