AWS prescriptive-guidance documentation change
Summary
Updated references from 'QuickSight' to 'Quick Suite' throughout the documentation, likely correcting a branding or naming inconsistency.
Security assessment
The changes are purely editorial, correcting the name of the service (QuickSight to Quick Suite) without introducing or modifying security-related content. No security mechanisms, vulnerabilities, or configurations are discussed in the modified sections.
Diff
diff --git a/prescriptive-guidance/latest/patterns/generate-db2-zos-data-insights-aws-mainframe-modernization-amazon-q-in-quicksight.md b/prescriptive-guidance/latest/patterns/generate-db2-zos-data-insights-aws-mainframe-modernization-amazon-q-in-quicksight.md index b481dacf7..798abe013 100644 --- a//prescriptive-guidance/latest/patterns/generate-db2-zos-data-insights-aws-mainframe-modernization-amazon-q-in-quicksight.md +++ b//prescriptive-guidance/latest/patterns/generate-db2-zos-data-insights-aws-mainframe-modernization-amazon-q-in-quicksight.md @@ -15 +15 @@ If your organization is hosting business-critical data in an IBM Db2 mainframe e -This pattern presents a solution for generating business insights and creating sharable narratives from mainframe data in IBM Db2 for z/OS tables. Mainframe data changes are streamed to [Amazon Managed Streaming for Apache Kafka (Amazon MSK)](https://docs.aws.amazon.com/msk/latest/developerguide/what-is-msk.html) topic using [AWS Mainframe Modernization Data Replication with Precisely](https://docs.aws.amazon.com/m2/latest/userguide/precisely.html). Using [Amazon Redshift streaming ingestion](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-streaming-ingestion.html), Amazon MSK topic data is stored in [Amazon Redshift Serverless](https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-whatis.html) data warehouse tables for analytics in Amazon QuickSight. +This pattern presents a solution for generating business insights and creating sharable narratives from mainframe data in IBM Db2 for z/OS tables. Mainframe data changes are streamed to [Amazon Managed Streaming for Apache Kafka (Amazon MSK)](https://docs.aws.amazon.com/msk/latest/developerguide/what-is-msk.html) topic using [AWS Mainframe Modernization Data Replication with Precisely](https://docs.aws.amazon.com/m2/latest/userguide/precisely.html). Using [Amazon Redshift streaming ingestion](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-streaming-ingestion.html), Amazon MSK topic data is stored in [Amazon Redshift Serverless](https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-whatis.html) data warehouse tables for analytics in Amazon Quick Suite. @@ -17 +17 @@ This pattern presents a solution for generating business insights and creating s -After the data is available in QuickSight, you can use natural language prompts with [Amazon Q in QuickSight](https://docs.aws.amazon.com/quicksight/latest/user/quicksight-gen-bi.html) to create summaries of the data, ask questions, and generate data stories. You don't have to write SQL queries or learn a business intelligence (BI) tool. +After the data is available in Quick Suite, you can use natural language prompts with [Amazon Q in QuickSight](https://docs.aws.amazon.com/quicksight/latest/user/quicksight-gen-bi.html) to create summaries of the data, ask questions, and generate data stories. You don't have to write SQL queries or learn a business intelligence (BI) tool. @@ -65 +65 @@ After you create the dashboard, you generate a data story that explains the insi - * The near real-time data in QuickSight depends on the refresh interval set for the Amazon Redshift database. + * The near real-time data in Quick Suite depends on the refresh interval set for the Amazon Redshift database. @@ -67 +67 @@ After you create the dashboard, you generate a data story that explains the insi - * Some AWS services aren’t available in all AWS Regions. For Region availability, see [AWS services by Region](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/). Amazon Q in QuickSight is currently not available in every Region that supports QuickSight. For specific endpoints, see the [Service endpoints and quotas](https://docs.aws.amazon.com/general/latest/gr/aws-service-information.html) page, and choose the link for the service. + * Some AWS services aren’t available in all AWS Regions. For Region availability, see [AWS services by Region](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/). Amazon Q in QuickSight is currently not available in every Region that supports Quick Suite. For specific endpoints, see the [Service endpoints and quotas](https://docs.aws.amazon.com/general/latest/gr/aws-service-information.html) page, and choose the link for the service. @@ -103 +103 @@ The diagram shows the following workflow: - 6. Amazon Redshift streaming ingestion provides low-latency, high-speed data ingestion from Amazon MSK to an Amazon Redshift Serverless database. A stored procedure in Amazon Redshift performs the mainframe change data (insert/update/deletes) reconciliation into Amazon Redshift tables. These Amazon Redshift tables serves as the data analytics source for QuickSight. + 6. Amazon Redshift streaming ingestion provides low-latency, high-speed data ingestion from Amazon MSK to an Amazon Redshift Serverless database. A stored procedure in Amazon Redshift performs the mainframe change data (insert/update/deletes) reconciliation into Amazon Redshift tables. These Amazon Redshift tables serves as the data analytics source for Quick Suite. @@ -105 +105 @@ The diagram shows the following workflow: - 7. Users access the data in QuickSight for analytics and insights. You can use Amazon Q in QuickSight to interact with the data by using natural language prompts. + 7. Users access the data in Quick Suite for analytics and insights. You can use Amazon Q in QuickSight to interact with the data by using natural language prompts. @@ -120 +120 @@ The diagram shows the following workflow: - * [Amazon QuickSight](https://docs.aws.amazon.com/quicksight/latest/user/welcome.html) is a cloud-scale business intelligence (BI) service that helps you visualize, analyze, and report your data in a single dashboard. This pattern uses the generative BI capabilities of [Amazon Q in QuickSight](https://docs.aws.amazon.com/quicksight/latest/user/working-with-quicksight-q.html). + * [Amazon Quick Suite](https://docs.aws.amazon.com/quicksight/latest/user/welcome.html) is a cloud-scale business intelligence (BI) service that helps you visualize, analyze, and report your data in a single dashboard. This pattern uses the generative BI capabilities of [Amazon Q in QuickSight](https://docs.aws.amazon.com/quicksight/latest/user/working-with-quicksight-q.html). @@ -138 +138 @@ The diagram shows the following workflow: -The code for this pattern is available in the GitHub [Mainframe_DataInsights_change_data_reconciliation](https://github.com/aws-samples/Mainframe_DataInsights_change_data_reconcilition) repository. The code is a stored procedure in Amazon Redshift. This stored procedure reconciles mainframe data changes (inserts, updates, and deletes) from Amazon MSK into the Amazon Redshift tables. These Amazon Redshift tables serve as the data analytics source for QuickSight. +The code for this pattern is available in the GitHub [Mainframe_DataInsights_change_data_reconciliation](https://github.com/aws-samples/Mainframe_DataInsights_change_data_reconcilition) repository. The code is a stored procedure in Amazon Redshift. This stored procedure reconciles mainframe data changes (inserts, updates, and deletes) from Amazon MSK into the Amazon Redshift tables. These Amazon Redshift tables serve as the data analytics source for Quick Suite. @@ -491 +491 @@ Create a materialized view.| To consume the data from the Amazon MSK topic in Am -Create target tables in Amazon Redshift.| Amazon Redshift tables provide the input for QuickSight. This pattern uses the tables `member_dtls` and `member_plans`, which match the source Db2 tables on the mainframe.To create the two tables in Amazon Redshift, run the following SQL commands in Amazon Redshift query editor v2: +Create target tables in Amazon Redshift.| Amazon Redshift tables provide the input for Quick Suite. This pattern uses the tables `member_dtls` and `member_plans`, which match the source Db2 tables on the mainframe.To create the two tables in Amazon Redshift, run the following SQL commands in Amazon Redshift query editor v2: @@ -515 +515 @@ Create target tables in Amazon Redshift.| Amazon Redshift tables provide the inp -Create a stored procedure in Amazon Redshift.| This pattern uses a stored procedure to sync-up change data (`INSERT`, `UPDATE`, `DELETE`) from the source mainframe to the target Amazon Redshift data warehouse table for analytics in QuickSight.To create the stored procedure in Amazon Redshift, use query editor v2 to run the stored procedure code that's in the GitHub repository.| Migration engineer +Create a stored procedure in Amazon Redshift.| This pattern uses a stored procedure to sync-up change data (`INSERT`, `UPDATE`, `DELETE`) from the source mainframe to the target Amazon Redshift data warehouse table for analytics in Quick Suite.To create the stored procedure in Amazon Redshift, use query editor v2 to run the stored procedure code that's in the GitHub repository.| Migration engineer @@ -530,2 +530,2 @@ Task| Description| Skills required -Set up QuickSight.| To set up QuickSight, follow the instructions in the [AWS documentation](https://docs.aws.amazon.com/quicksight/latest/user/setting-up.html).| Migration engineer -Set up a secure connection between QuickSight and Amazon Redshift.| To set up secure a connection between QuickSight and Amazon Redshift, do the following +Set up Quick Suite.| To set up Quick Suite, follow the instructions in the [AWS documentation](https://docs.aws.amazon.com/quicksight/latest/user/setting-up.html).| Migration engineer +Set up a secure connection between Quick Suite and Amazon Redshift.| To set up secure a connection between Quick Suite and Amazon Redshift, do the following @@ -533 +533 @@ Set up a secure connection between QuickSight and Amazon Redshift.| To set up se - 1. To authorize connections from QuickSight to Amazon Redshift, open the Amazon Redshift console, and add an inbound rule in the Amazon Redshift security group. The rule should allow traffic to port 5439 (the default Redshift port) from the CIDR range where you set up QuickSight. For a list of AWS Regions and their IP addresses, see [Supported AWS Regions for QuickSight](https://docs.aws.amazon.com/quicksight/latest/user/regions-qs.html). + 1. To authorize connections from Quick Suite to Amazon Redshift, open the Amazon Redshift console, and add an inbound rule in the Amazon Redshift security group. The rule should allow traffic to port 5439 (the default Redshift port) from the CIDR range where you set up Quick Suite. For a list of AWS Regions and their IP addresses, see [Supported AWS Regions for Quick Suite](https://docs.aws.amazon.com/quicksight/latest/user/regions-qs.html). @@ -537 +537 @@ Set up a secure connection between QuickSight and Amazon Redshift.| To set up se -Create a dataset for QuickSight.| To create a dataset for QuickSight from Amazon Redshift, do following: +Create a dataset for Quick Suite.| To create a dataset for Quick Suite from Amazon Redshift, do following: @@ -539 +539 @@ Create a dataset for QuickSight.| To create a dataset for QuickSight from Amazon - 1. On the QuickSight console, in the navigation pane, choose **Datasets**. + 1. On the Quick Suite console, in the navigation pane, choose **Datasets**. @@ -555 +555 @@ Create a dataset for QuickSight.| To create a dataset for QuickSight from Amazon -Join the dataset.| To create analytics in QuickSight, join the two tables by following the instructions in the [AWS documentation](https://docs.aws.amazon.com/quicksight/latest/user/joining-data.html#create-a-join).In the **Join Configuration** pane, choose **Left** for **Join type**. Under **Join clauses** , use `memberid from member_plans = memberid from members_details`.| Migration engineer +Join the dataset.| To create analytics in Quick Suite, join the two tables by following the instructions in the [AWS documentation](https://docs.aws.amazon.com/quicksight/latest/user/joining-data.html#create-a-join).In the **Join Configuration** pane, choose **Left** for **Join type**. Under **Join clauses** , use `memberid from member_plans = memberid from members_details`.| Migration engineer @@ -560 +560 @@ Set up Amazon Q in QuickSight.| To set up the Amazon Q in QuickSight Generative -Analyze mainframe data and build a visual dashboard.| To analyze and visualize your data in QuickSight, do the following: +Analyze mainframe data and build a visual dashboard.| To analyze and visualize your data in Quick Suite, do the following: @@ -598 +598 @@ Issue| Solution -For QuickSight to Amazon Redshift dataset creation, `Validate Connection` has faled.| +For Quick Suite to Amazon Redshift dataset creation, `Validate Connection` has faled.| @@ -600 +600 @@ For QuickSight to Amazon Redshift dataset creation, `Validate Connection` has fa - 1. Confirm that the security group attached to the Amazon Redshift Serverless instance allows inbound traffic from the IP address range associated with the Region where you set up QuickSight. + 1. Confirm that the security group attached to the Amazon Redshift Serverless instance allows inbound traffic from the IP address range associated with the Region where you set up Quick Suite.