This Guidance helps customers authorize, manage, and audit access to data. Deriving new business insights requires a well-defined, value-oriented strategy, and a coordinated execution with the business and IT. AWS solutions provides the ability to enforce controls for services that access data such as Amazon Redshift, Amazon EMR, Amazon Athena, and Amazon SageMaker.
Architecture Diagram
Step 1
Identify and configure (or activate) the data sources. Transfer from SAP application to AWS services. Then configure the Operating Data Provisioning (ODP) for extraction in the SAP Gateway of your SAP system.
Step 2
Create the OData system connection from Amazon AppFlow to SAP source system. This can be via AWS PrivateLink for SAP on AWS/connect with AWS via VPN/AWS Direct Connect, or over the internet.
Step 3
In Amazon AppFlow, create the flow using the SAP source created in step 2. Run the flow to extract data from SAP and save to an Amazon Simple Storage Service (Amazon S3) bucket.
Step 4
Use AWS Glue DataBrew to cleanse and optimize the format of your SAP data. Save the transformed data in another Amazon S3 bucket. With AWS Glue crawler, create a data catalog entry with metadata for the extracted SAP data in another Amazon S3 bucket. Use the Amazon S3 Intelligent-Tiering storage class to automatically optimize storage costs.
Step 5
Use Amazon Athena, an interactive query service, to analyze the data in Amazon S3 using standard SQL.
Step 6
Visualize the dataset in Amazon QuickSight with Athena as the data source.
Step 7
Create dashboards to visualize the audit and compliance data requirements. For joint visualization, extend the archive data using SAP Analytics Cloud (SAC).
Step 1
Identify and configure (or activate) the data sources. Transfer from SAP application to AWS services. Then configure the Operating Data Provisioning (ODP) for extraction in the SAP Gateway of your SAP system.
Step 2
Create the OData system connection from Amazon AppFlow to SAP source system. This can be via AWS PrivateLink for SAP on AWS/connect with AWS via VPN/AWS Direct Connect, or over the internet.
Step 3
In Amazon AppFlow, create the flow using the SAP source created in step 2. Run the flow to extract data from SAP and save to an Amazon Simple Storage Service (Amazon S3) bucket.
Step 4
Use AWS Glue DataBrew to cleanse and optimize the format of your SAP data. Save the transformed data in another Amazon S3 bucket. With AWS Glue crawler, create a data catalog entry with metadata for the extracted SAP data in another Amazon S3 bucket. Use the Amazon S3 Intelligent-Tiering storage class to automatically optimize storage costs.
Step 5
Use Amazon Athena, an interactive query service, to analyze the data in Amazon S3 using standard SQL.
Step 6
Visualize the dataset in Amazon QuickSight with Athena as the data source.
Step 7
Create dashboards to visualize the audit and compliance data requirements. For joint visualization, extend the archive data using SAP Analytics Cloud (SAC).
Well-Architected Pillars
The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.
The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.
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Operational ExcellenceRead the Operational Excellence whitepaper
Reference SAP system data extraction to AWS is deployed with code. Incorporate this automation to your own development pipeline to enable iteration and consistent deployments across your SAP landscape. Observability is derived from the managed services used for processing. Process level metrics, logs and dashboards are available from Amazon CloudWatch.
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SecurityRead the Security whitepaper
The serverless components in the architecture are protected with AWS Identity and Access Management (IAM) for secure validation of user identity. The managed services only have access to the data that is specified. Access to the SAP workload is through Amazon AppFlow. Amazon AppFlow supports PrivateLink. Data is encrypted in transit and at rest. Amazon Redshift can be deployed into a customer’s Virtual Private Cloud (VPC).
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ReliabilityRead the Reliability whitepaper
All the serverless components are highly available. All non-SAP components automatically scale. Amazon AppFlow moves large volumes of data without reducing it into multiple batches to increase reliability. Amazon Redshift continuously monitors health, automatically replicates data from failed drives, and replaces nodes as necessary for fault tolerance.
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Performance EfficiencyRead the Performance Efficiency whitepaper
By leveraging serverless technologies, provision only the exact resources you use. Using Amazon S3 as the corporate data memory optimises the storage of the architecture with the processing of the data performed in Amazon Redshift. For improved performance and agility, configure multiple flows in Amazon AppFlow for different groups of business data.
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Cost OptimizationRead the Cost Optimization whitepaper
By utilizing serverless technologies, you only pay for the resources you use. To further optimize cost, make sure you are extracting only the business data group that you need. To further optimize cost, minimize the number of flows being executed based on the granularity of your reporting needs. Amazon S3 lifecycle policies can be put in place for data.
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SustainabilityRead the Sustainability whitepaper
By utilizing managed services and dynamic scaling, you minimize the environmental impact of the backend services. As new options become available for Amazon AppFlow, make sure these are adopted to further optimize the volume and frequency of extraction. Reducing the quantity and frequency of extraction will improve sustainability as well as help reduce cost and improve performance.
Related Content
Disclaimer
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