Summary
In this chapter, we have discussed what big data is, the characteristics of big data, what a data lake is, why we need data lakes, and how a data lake can be built on Amazon S3 by providing an overview of the benefits of data lakes, the different layers of a data lake, and the best practices for building a data lake on Amazon S3. We also provided details on organizing and managing the data within a data lake on S3, including using features such as file formats, partitions, S3 lifecycle management, Amazon S3 Intelligent-Tiering, and so on. The chapter also discussed some challenges and considerations when building a data lake on Amazon S3, such as cost and performance.
In the next chapter, we are going to learn about AWS Glue. AWS Glue is a data integration service that lets you bring data from different data sources and allows you to perform ETL on top of it using frameworks such as Apache Spark and Python.