Presto & Data Science: Getting Data Into the Hands of Data Scientists (Faster)

Data scientists often face inefficiencies due to the significant time spent on data collection and preparation, which can occupy up to half of their workday, drastically reducing the time available for analytics and model building. Presto, a high-performance SQL query engine, addresses this issue by allowing data scientists to remain in familiar environments like R Studio or Jupyter while accessing disparate data sources without the need for extensive ETL processes. Starburst, an enterprise-ready distribution of Presto, enhances this capability by enabling fast, comprehensive data queries across various data repositories, thereby improving the speed and quality of analytics and freeing data scientists to focus on more creative and impactful projects. This approach is particularly beneficial in industries such as banking, financial services, and pharmaceuticals, where timely and detailed data analysis is crucial, and it aligns with a growing preference for using open-source tools to maximize efficiency and innovation.