This resource is no longer available
According to Forbes, data scientists spend up to 80% of their time finding, retrieving, and preparing data for analysis and trainings—a sad state of affairs, considering that 76% of these scientists view data preparation as the least enjoyable part of their work.
Fortunately, more advanced data science pipelines are helping data scientists access data and integrated platforms help prepare it for use in ML projects or in analytics.
Read this short white paper to learn how Snowflake’s Cloud Data Platform allows data intensive machine learning projects to thrive at scale, enables data sharing across architectures, and supports better performance and faster analytics.