Several data sciences and analysis tasks can be automated with “autodata tools” to improve productivity and quality. In this post, Adam Marcus describes OSS autodata tools that transform data science and analysis workflows into a series of declarative steps. These tools automate processes like data ingestion into a data frame or database, exploratory data analysis; feature engineering; and model building. He predicts that autodata primitives will be composed into more complex automations; new tools to monitor and evaluate autodata pipelines will emerge; autodata interfaces will become increasingly declarative.