The Shift To Predictive And Prescriptive Analytics Accelerates

This idea comes from a recent report from data cloud platform company Snowflake on data science and analytics trends. Data analytics has traditionally been used to understand what happened. But there is growing use of data analytics and machine learning technology to predict what will happen and offer suggested prescriptive responses – even automated actions – to the analytical results, turning data into “an actionable asset.”

This shift is accelerating thanks to the growing availability and adoption of easy-to-use machine learning tools by analysts and data scientists, the ability to manage and deploy at scale machine learning features with next-generation feature stores, and a new generation of distributed frameworks for training and deploying machine learning models.

More frequent releases of machine learning tools and libraries are a factor here, as are consolidated platforms (like Snowflake) that are closing the gap between analytics and machine learning.