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AWS Solutions Library

Guidance for Accelerating Analytics on AWS

Overview

This Guidance deploys a configurable, end-to-end set of AWS data and analytics services to visualize your data. Previously, integrating multiple data and analytics components required manually deploying and configuring each service, often a time-consuming process needing engineers to instrument. This Guidance is especially helpful to quickly iterate, publish, and test analytics projects on the way to wider-scale implementations. With Accelerating Analytics on AWS, you can launch a single  AWS CloudFormation template  that deploys and configures multiple, integrated AWS data and analytics services to quickly scale users’ access to data and insights more quickly and with less resources.

How it works

This Guidance helps you quickly deploy a data analytics stack using AWS services. In this diagram, an administrator creates a storage bucket and uploads files that can be processed for data analysis and visualization.

Download the architecture diagram

Well-Architected Pillars

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.

The AWS services used in this Guidance support logging information in Amazon CloudWatch or AWS CloudTrail that can be tracked and reviewed for additional customization. This enables a fast and easy way to review errors and respond to incidents appropriately.

Read the Operational Excellence whitepaper

The AWS Glue database and table created in this Guidance are secured using Lake Formation, and access is granted only to the IAM role used by Quicksight. This allows for secure authentication and authorization for people and machine access. 

The resources provisioned in this Guidance are private by default, and can only be modified with IAM identity-based policies.

Read the Security whitepaper

Since AWS services used in this Guidance are serverless, use AWS managed endpoints and DNS, the implementation can depend on the high availability and resiliency to failures that are inherent in AWS services. 

AWS CloudFormation automates deployment and provisioning of resources. Upon failure of one resource, the implementation rolls back all other provisioned resources, ensuring you have a reliable application-level architecture. 

Additionally, CloudFormation logs resource provisioning and errors that can be accessed using CloudTrail and CloudWatch. QuickSight sends an email to notify account administrators when significant events occur.

Read the Reliability whitepaper

The services selected for this Guidance are purpose-built to handle advanced analytics. For example, QuickSight is an AWS managed serverless business intelligence (BI) service that integrates with Athena to query data in Amazon S3. 

A QuickSight analysis, where you analyze and visualize your data, is created when this Guidance is deployed, helping you gain insights from your data. Based on Athena tables, also created by this Guidance, you can experiment and create additional tables to query data in Amazon S3 or other supported data sources.

Read the Performance Efficiency whitepaper

This Guidance uses managed services that deploy a pay-as-you-go approach, removing the need to maintain overhead and reduce cost. AWS services used in this Guidance are also provisioned in the same AWS Region to reduce data transfer charges, whereas QuickSight does not accrue any data transfer charges. 

All services in this Guidance are serverless and do not require running for an extended period of time. To ensure this Guidance scales to continually match the demand with the minimum resources, it deploys an Amazon S3 bucket that contains only customer provisioned data. The AWS Glue crawler runs once per day to check for new data, and Athena is invoked only when using QuickSight.

Read the Cost Optimization whitepaper

This Guidance invokes Athena only when users interact with the corresponding data sets in QuickSight, ensuring limited provisioning of resources. Additionally, Amazon S3 and Athena automatically scale to accommodate data that you provide. 

Architecture patterns that maintain consistently high utilization of deployed resources are implemented with this Guidance. For example, the AWS Glue crawler is only invoked once every day to crawl customer data in Amazon S3 buckets and to update the Glue Catalog. Finally, this Guidance uses serverless AWS services that do not require continuous hardware provisioning, making it a more sustainable architecture.

Read the Sustainability whitepaper

Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

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