Summary

In this chapter, we discussed how you can use Redshift ML to generate forecasting models using Amazon Forecast by creating the model for Forecast Model_Type. You learned about what forecasting is and how time-series data is used to generate different models for different quantiles. We also looked at different quantiles and talked briefly about different optimization metrics.

We showed how forecast models can be used to predict the future quantity sale for a retailer use case and how they can be used to balance the effect of over-forecasting and under-forecasting.

In the next chapter, we will look at operational and optimization considerations.