Accelerating Data Science with Trino

Trino, previously known as Presto SQL, and Starburst are tools designed to enhance the efficiency and ease of data scientists' roles by providing faster access to data and simplifying data management. At the Datanova conference, discussions highlighted how these tools support a transition from traditional monolithic data management to a distributed Data Mesh approach, enabling seamless and direct data access. For data scientists, this means reduced cycle time in model development and the ability to ask more questions and gain deeper insights from their data. Trino's SQL-based approach allows for efficient data preprocessing, facilitating rapid exploration and analysis, which is crucial for building predictive models. The tools were initially used at Facebook for handling large data sets, particularly for marketing and financial services applications, and they help in data profiling, exploration, and reducing data preparation time through SQL-driven processes. Additionally, Trino integrates with DevOps practices without altering the basic approach, allowing operational data to be treated as source data, thereby enhancing the overall efficiency and productivity of data science tasks.