AWS whitepapers documentation change
Summary
Updated product name from 'Amazon Quick Suite' to 'Amazon Quick' throughout the document
Security assessment
The changes are purely cosmetic rebranding updates (changing 'Suite' to a shorter name). No security vulnerabilities, configurations, or features are mentioned or modified. SPICE engine details, data persistence, and sharing mechanisms remain unchanged with no security implications.
Diff
diff --git a/whitepapers/latest/big-data-analytics-options/amazon-quicksight.md b/whitepapers/latest/big-data-analytics-options/amazon-quicksight.md index 7d38b84dd..78dbec85e 100644 --- a//whitepapers/latest/big-data-analytics-options/amazon-quicksight.md +++ b//whitepapers/latest/big-data-analytics-options/amazon-quicksight.md @@ -9 +9 @@ This whitepaper is for historical reference only. Some content might be outdated -# Amazon Quick Suite +# Amazon Quick @@ -11 +11 @@ This whitepaper is for historical reference only. Some content might be outdated -Amazon Quick Suite is a scalable, serverless, embeddable, machine learning-powered business intelligence (BI) service built for the cloud. It makes it easy for all employees within an organization to build visualizations, perform ad hoc analysis, and quickly get business insights from their data, anytime, on any device. It can connect to a wide variety of data sources including flat files such as CSV and Excel, access on-premises databases including Oracle, SQL Server, MySQL, and PostgreSQL, AWS resources such as Amazon RDS databases, Amazon Redshift, Amazon Athena, and Amazon S3, and SaaS solutions such as Salesforce, ServiceNow, and Adobe Analytics. Amazon Quick Suite enables organizations to scale their business analytics capabilities to hundreds of thousands of users, and delivers fast and responsive query performance by using a robust in-memory engine (SPICE). +Amazon Quick is a scalable, serverless, embeddable, machine learning-powered business intelligence (BI) service built for the cloud. It makes it easy for all employees within an organization to build visualizations, perform ad hoc analysis, and quickly get business insights from their data, anytime, on any device. It can connect to a wide variety of data sources including flat files such as CSV and Excel, access on-premises databases including Oracle, SQL Server, MySQL, and PostgreSQL, AWS resources such as Amazon RDS databases, Amazon Redshift, Amazon Athena, and Amazon S3, and SaaS solutions such as Salesforce, ServiceNow, and Adobe Analytics. Amazon Quick enables organizations to scale their business analytics capabilities to hundreds of thousands of users, and delivers fast and responsive query performance by using a robust in-memory engine (SPICE). @@ -13 +13 @@ Amazon Quick Suite is a scalable, serverless, embeddable, machine learning-power -Amazon Quick Suite is built with "[SPICE](https://aws.amazon.com/about-aws/whats-new/2020/07/amazon-quicksight-spice-data-engine-supports-data-sets-250m-rows/)" – a Super-fast, Parallel, In-memory Calculation Engine. Built from the ground up for the cloud, SPICE uses a combination of columnar storage, in-memory technologies enabled through the latest hardware innovations, and machine code generation to run interactive queries on large datasets and get rapid responses. SPICE supports rich calculations to help you derive valuable insights from your analysis without worrying about provisioning or managing infrastructure. Data in SPICE is persisted until it is explicitly deleted by the user. SPICE also automatically replicates data for high availability and enables Amazon Quick Suite to scale to hundreds of thousands of users who can all simultaneously perform fast interactive analysis across a wide variety of AWS data sources. +Amazon Quick is built with "[SPICE](https://aws.amazon.com/about-aws/whats-new/2020/07/amazon-quicksight-spice-data-engine-supports-data-sets-250m-rows/)" – a Super-fast, Parallel, In-memory Calculation Engine. Built from the ground up for the cloud, SPICE uses a combination of columnar storage, in-memory technologies enabled through the latest hardware innovations, and machine code generation to run interactive queries on large datasets and get rapid responses. SPICE supports rich calculations to help you derive valuable insights from your analysis without worrying about provisioning or managing infrastructure. Data in SPICE is persisted until it is explicitly deleted by the user. SPICE also automatically replicates data for high availability and enables Amazon Quick to scale to hundreds of thousands of users who can all simultaneously perform fast interactive analysis across a wide variety of AWS data sources. @@ -19 +19 @@ QuickSight leverages the AWS proven ML capabilities, making it easy for BI teams -Amazon Quick Suite is an ideal Business Intelligence tool, allowing end users to create visualizations that provide insight into their data to help them make better business decisions. Amazon Quick Suite can be used to do the following: +Amazon Quick is an ideal Business Intelligence tool, allowing end users to create visualizations that provide insight into their data to help them make better business decisions. Amazon Quick can be used to do the following: @@ -46 +46 @@ Amazon Quick Suite is an ideal Business Intelligence tool, allowing end users to -Amazon Quick Suite has two different editions for pricing; _Standard_ edition and _Enterprise_ edition. +Amazon Quick has two different editions for pricing; _Standard_ edition and _Enterprise_ edition. @@ -61 +61 @@ For large-scale deployments and public embedding, there is a Session capacity pr -Amazon Quick Suite is built with [SPICE](https://aws.amazon.com/about-aws/whats-new/2020/07/amazon-quicksight-spice-data-engine-supports-data-sets-250m-rows/). Built from the ground up for the cloud, SPICE uses a combination of columnar storage, in-memory technologies enabled through the latest hardware innovations, and machine code generation to run interactive queries on large datasets and get rapid responses. +Amazon Quick is built with [SPICE](https://aws.amazon.com/about-aws/whats-new/2020/07/amazon-quicksight-spice-data-engine-supports-data-sets-250m-rows/). Built from the ground up for the cloud, SPICE uses a combination of columnar storage, in-memory technologies enabled through the latest hardware innovations, and machine code generation to run interactive queries on large datasets and get rapid responses. @@ -65 +65 @@ Amazon Quick Suite is built with [SPICE](https://aws.amazon.com/about-aws/whats- -SPICE automatically replicates data for high availability and enables Amazon Quick Suite to scale to hundreds of thousands of users who can all simultaneously perform fast interactive analysis across a wide variety of AWS data sources. +SPICE automatically replicates data for high availability and enables Amazon Quick to scale to hundreds of thousands of users who can all simultaneously perform fast interactive analysis across a wide variety of AWS data sources. @@ -69 +69 @@ SPICE automatically replicates data for high availability and enables Amazon Qui -Amazon Quick Suite is a fully managed service and it internally takes care of scaling to meet the demands of your end users. With Amazon Quick Suite you don’t need to worry about scale. You can seamlessly grow your data from a few hundred megabytes to many terabytes of data without managing any infrastructure. +Amazon Quick is a fully managed service and it internally takes care of scaling to meet the demands of your end users. With Amazon Quick you don’t need to worry about scale. You can seamlessly grow your data from a few hundred megabytes to many terabytes of data without managing any infrastructure. @@ -73 +73 @@ Amazon Quick Suite is a fully managed service and it internally takes care of sc -Amazon Quick Suite can connect to a wide variety of data sources including flat files (CSV, TSV, CLF, ELF), connect to on-premises databases like SQL Server, MySQL, and PostgreSQL, and AWS data sources including Amazon RDS, Amazon Aurora, Amazon Redshift, Amazon Athena and Amazon S3, and SaaS, applications like Salesforce. You can also export data from any type of chart or graph and the export contains only the data in the fields that are currently visible in the selected visualization. +Amazon Quick can connect to a wide variety of data sources including flat files (CSV, TSV, CLF, ELF), connect to on-premises databases like SQL Server, MySQL, and PostgreSQL, and AWS data sources including Amazon RDS, Amazon Aurora, Amazon Redshift, Amazon Athena and Amazon S3, and SaaS, applications like Salesforce. You can also export data from any type of chart or graph and the export contains only the data in the fields that are currently visible in the selected visualization. @@ -75 +75 @@ Amazon Quick Suite can connect to a wide variety of data sources including flat -You can [share an analysis](https://docs.aws.amazon.com/quicksight/latest/user/sharing-analyses.html), dashboard, or story by choosing **Share with users and groups in your account** on the application bar from the Amazon Quick Suite service interface. You can select the recipients (email address, username, or group name), permission levels, and other options, before sharing the content with others. +You can [share an analysis](https://docs.aws.amazon.com/quicksight/latest/user/sharing-analyses.html), dashboard, or story by choosing **Share with users and groups in your account** on the application bar from the Amazon Quick service interface. You can select the recipients (email address, username, or group name), permission levels, and other options, before sharing the content with others. @@ -79 +79 @@ You can [share an analysis](https://docs.aws.amazon.com/quicksight/latest/user/s -While Amazon Quick Suite can perform some transformations, it is not a full-fledged ETL tool. AWS offers AWS Glue, which is a fully managed ETL service that makes it easy for customers to prepare and load their data for analytics. +While Amazon Quick can perform some transformations, it is not a full-fledged ETL tool. AWS offers AWS Glue, which is a fully managed ETL service that makes it easy for customers to prepare and load their data for analytics.