AWS managedservices documentation change
Summary
Updated document title and section headers from 'FAQs' to 'FAQ' (plural to singular), and corrected a link label to 'AWS Glue FAQ'
Security assessment
Changes are grammatical/formatting improvements without altering security-related content. The security references to data access policies and sensitive data protection remain unchanged.
Diff
diff --git a/managedservices/latest/userguide/lake-formation.md b/managedservices/latest/userguide/lake-formation.md index d077ae71c..60de765d8 100644 --- a//managedservices/latest/userguide/lake-formation.md +++ b//managedservices/latest/userguide/lake-formation.md @@ -5 +5 @@ -Lake Formation in AWS Managed Services FAQs +Lake Formation in AWS Managed Services FAQ @@ -11 +11 @@ Use AMS Self-Service Provisioning (SSP) mode to access AWS Lake Formation capabi -Creating a data lake with Lake Formation is as simple as defining data sources and what data access and security policies you want to apply. Lake Formation then helps you collect and catalog data from databases and object storage, move the data into your new Amazon S3 data lake, clean and classify your data using machine learning algorithms, and secure access to your sensitive data. Your users can access a centralized data catalog (for details, see [AWS Glue FAQs](https://aws.amazon.com/glue/faqs/#AWS_Glue_Data_Catalog/)) that describes available data sets and their appropriate usage. Your users then leverage these data sets with their choice of analytics and machine learning services, like [Amazon Redshift](https://aws.amazon.com/redshift/), [Amazon Athena](https://aws.amazon.com/athena/), and (in beta) [Amazon EMR](https://aws.amazon.com/emr/) for Apache Spark. Lake Formation builds on the capabilities available in [AWS Glue](https://aws.amazon.com/glue/). +Creating a data lake with Lake Formation is as simple as defining data sources and what data access and security policies you want to apply. Lake Formation then helps you collect and catalog data from databases and object storage, move the data into your new Amazon S3 data lake, clean and classify your data using machine learning algorithms, and secure access to your sensitive data. Your users can access a centralized data catalog (for details, see [AWS Glue FAQ](https://aws.amazon.com/glue/faqs/#AWS_Glue_Data_Catalog/)) that describes available data sets and their appropriate usage. Your users then leverage these data sets with their choice of analytics and machine learning services, like [Amazon Redshift](https://aws.amazon.com/redshift/), [Amazon Athena](https://aws.amazon.com/athena/), and (in beta) [Amazon EMR](https://aws.amazon.com/emr/) for Apache Spark. Lake Formation builds on the capabilities available in [AWS Glue](https://aws.amazon.com/glue/). @@ -15 +15 @@ To learn more, see [AWS Lake Formation](https://aws.amazon.com/lake-formation/). -## Lake Formation in AWS Managed Services FAQs +## Lake Formation in AWS Managed Services FAQ