Summary
In this chapter, we learned that Domo provides a product that's integrated with AWS SageMaker Autopilot to automate ML modeling tasks. We learned how to prepare a dataset and train and retrain models. Then, we deployed the model via an ETL job and ran new data through it to get a predicted vehicle price from the model. Finally, we became aware of the capability to run Jupyter Workspaces in the Domo cloud. This combination of technologies makes the process complex of creating ML-based predictive modeling accessible to the typical analyst. This is another way that Domo is democratizing the analytics process.
In the next chapter, we'll look at securing assets in Domo.
