Although structured data remains the backbone for many data platforms, increasingly unstructured or semistructured data is used to enrich existing information or to create new insights. Amazon Athena enables you to analyze a wide variety of data. This includes tabular data in comma-separated value (CSV) or Apache Parquet files, data extracted from log files using regular expressions, and JSON-formatted data. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
To determine the key noun phrases used in text, use the Amazon Comprehend operation. To detect the key noun phrases in up to 25 documents in a batch, use the operation. For more information, see .
How to use Amazon QuickSight and AWS machine learning to help you make data-driven decisions.
This article aims to demonstrate some of the many uses of the Fn::Sub syntax in the AWS CloudFormation service. Topics include:
Basic Fn::Sub and !Sub syntax
Short and long form syntax
Nested Sub and ImportValue statements
About a year ago (Sept 2016, along with YAML support) AWS added a new intrinsic function to CloudFormation: Fn::Sub. This greatly improved string concatenation in CloudFormation.
AWS : CloudFormation Bootstrap UserData/Metadata