AWS whitepapers documentation change
Summary
Updated references from 'Amazon QuickSight' to 'QuickSight' throughout the document for consistency
Security assessment
The changes are purely branding/naming convention updates (removing 'Amazon' prefix from QuickSight). No security-related content was added, modified, or removed. The security mentions in the DataZone section remain unchanged.
Diff
diff --git a/whitepapers/latest/aws-overview/analytics.md b/whitepapers/latest/aws-overview/analytics.md index 8b18b5c9c..91f89a7b2 100644 --- a//whitepapers/latest/aws-overview/analytics.md +++ b//whitepapers/latest/aws-overview/analytics.md @@ -5 +5 @@ -Amazon AthenaAmazon CloudSearchAmazon DataZoneAmazon EMR Amazon FinSpaceAmazon KinesisAmazon Data FirehoseAmazon Managed Service for Apache FlinkAmazon Kinesis Data StreamsAmazon Kinesis Video StreamsAmazon OpenSearch ServiceAmazon OpenSearch ServerlessAmazon RedshiftAmazon Redshift ServerlessAmazon QuickSightAWS Clean RoomsAWS Data ExchangeAWS Data PipelineAWS Entity ResolutionAWS GlueAWS Lake FormationAmazon Managed Streaming for Apache Kafka (Amazon MSK) +Amazon AthenaAmazon CloudSearchAmazon DataZoneAmazon EMR Amazon FinSpaceAmazon KinesisAmazon Data FirehoseAmazon Managed Service for Apache FlinkAmazon Kinesis Data StreamsAmazon Kinesis Video StreamsAmazon OpenSearch ServiceAmazon OpenSearch ServerlessAmazon RedshiftAmazon Redshift ServerlessQuickSightAWS Clean RoomsAWS Data ExchangeAWS Data PipelineAWS Entity ResolutionAWS GlueAWS Lake FormationAmazon Managed Streaming for Apache Kafka (Amazon MSK) @@ -45 +45 @@ Each service is described after the diagram. To help you decide which service be - * Amazon QuickSight + * QuickSight @@ -80 +80 @@ Athena is out-of-the-box integrated with AWS Glue Data Catalog, allowing you to -[Amazon DataZone](https://aws.amazon.com/datazone/) is a data management service that you can use to publish data and make it available to the business data catalog through your personalized web application. You can access your data more securely regardless of where it is stored—on AWS, on premises, or in SaaS applications such as Salesforce. Amazon DataZone simplifies your experience across AWS services such as Amazon Redshift, Amazon Athena, AWS Glue, AWS Lake Formation, and Amazon QuickSight. +[Amazon DataZone](https://aws.amazon.com/datazone/) is a data management service that you can use to publish data and make it available to the business data catalog through your personalized web application. You can access your data more securely regardless of where it is stored—on AWS, on premises, or in SaaS applications such as Salesforce. Amazon DataZone simplifies your experience across AWS services such as Amazon Redshift, Amazon Athena, AWS Glue, AWS Lake Formation, and QuickSight. @@ -138 +138 @@ The [vector engine for Amazon OpenSearch Serverless](https://aws.amazon.com/open -## Amazon QuickSight +## QuickSight @@ -140 +140 @@ The [vector engine for Amazon OpenSearch Serverless](https://aws.amazon.com/open -[Amazon QuickSight](https://aws.amazon.com/quicksight/) is a fast, cloud-powered business intelligence (BI) service that makes it easy for you to deliver insights to everyone in your organization. QuickSight lets you create and publish interactive dashboards that can be accessed from browsers or mobile devices. You can embed dashboards into your applications, providing your customers with powerful self-service analytics. Amazon QuickSight easily scales to tens of thousands of users without any software to install, servers to deploy, or infrastructure to manage. +[QuickSight](https://aws.amazon.com/quicksight/) is a fast, cloud-powered business intelligence (BI) service that makes it easy for you to deliver insights to everyone in your organization. QuickSight lets you create and publish interactive dashboards that can be accessed from browsers or mobile devices. You can embed dashboards into your applications, providing your customers with powerful self-service analytics. QuickSight easily scales to tens of thousands of users without any software to install, servers to deploy, or infrastructure to manage. @@ -178 +178 @@ However, setting up and managing data lakes today involves a lot of manual, comp -Creating a data lake with Lake Formation is as simple as defining where your data resides and what data access and security policies you want to apply. Lake Formation then collects and catalogs data from databases and object storage, moves the data into your new Amazon S3 data lake, cleans and classifies data using ML algorithms, and secures access to your sensitive data. Your users can then access a centralized catalog of data which describes available data sets and their appropriate usage. Your users then leverage these data sets with their choice of analytics and ML services, such as Amazon EMR for Apache Spark, Amazon Redshift, Amazon Athena, SageMaker AI, and Amazon QuickSight. +Creating a data lake with Lake Formation is as simple as defining where your data resides and what data access and security policies you want to apply. Lake Formation then collects and catalogs data from databases and object storage, moves the data into your new Amazon S3 data lake, cleans and classifies data using ML algorithms, and secures access to your sensitive data. Your users can then access a centralized catalog of data which describes available data sets and their appropriate usage. Your users then leverage these data sets with their choice of analytics and ML services, such as Amazon EMR for Apache Spark, Amazon Redshift, Amazon Athena, SageMaker AI, and QuickSight.