Summary

In this chapter, we showcased how you can load data into your Amazon Redshift Serverless database using three different tools and methods, by using the query editor v GUI interface, the Redshift COPY command to load the data, and the Redshift Data API using Python in a Jupyter notebook. All three methods are efficient and easy to use for your different use cases.

We also talked about some of the best practices for the COPY command to make efficient use of it.

In the next chapter, we will start with our first topic concerning Amazon Redshift machine learning, and you will see how you can leverage it in your Amazon Redshift Serverless data warehouse.