Chapter 6: AWS Services for Data Processing
In the previous chapter, we learned about several ways of storing data in AWS. In this chapter, we will explore the techniques for using that data and gaining some insight from the data. There are use cases where you have to process your data or load the data to a hive data warehouse to query and analyze the data. If you are on AWS and your data is in S3, then you have to create a table in hive on AWS EMR to query them. To provide the same as a managed service, AWS has a product called Athena, where you have to create a data catalog and query your data on S3. If you need to transform the data, then AWS Glue is the best option to transform and restore it to S3. Let's imagine a use case where we need to stream the data and create analytical reports on that data. For such scenarios, we can opt for AWS Kinesis Data Streams to stream data and store it in S3. Using Glue, the same data can be copied to Redshift for further analytical utilization...