Overview
Automated Data Analytics on AWS allows you to derive meaningful insights from data in a matter of minutes through a simple and intuitive user interface.
This AWS Solution helps you to easily consolidate data distributed across silos, apply fine-grained governance controls, and query data through a tailored user experience. It is quickly deployed to an AWS account through a single click, removing the need for deep technical expertise.
What's new
- Create a budget with a cost limit to track costs and usage, and receive notifications if the costs exceed specified certain thresholds.
- Extend solution’s capabilities by integrating with Apache Superset for visualizing and analyzing data ingested into the solution, and source data connectors from ADA to additional SaaS sources available through Amazon AppFlow.
To find out about other new features, refer to the Revisions page.
Benefits
Ready to use out of the box, no need to build your own platform. If you are early in your data journey, get started quickly with the solution, and expand your capabilities over time.
Removes the heavy lifting of joining and managing disparate datasets.
Anyone with SQL skills can quickly and easily derive insights from their data.
Users can share datasets and queries across teams with flexible controls to enforce access protection.
Technical details
You can automatically deploy this architecture using the implementation guide and the accompanying AWS CloudFormation template.
Read more about the different data connectors supported by the solution, how to access and interact with the solution APIs, and how to extend the solution's capabilities with third-party extensions.
Step 1
The AWS CloudFormation template provisions the following infrastructure and services provided by the solution.
Step 2
Amazon CloudFront and AWS WAF for static website hosting distribution and protection. An Amazon DynamoDB table is used to manage and provide persistent notifications in the user interface.
Step 3
Federated Identity: An Amazon Cognito user pool manages federating and storing users from external identity providers (IDPs).
Step 4
A DynamoDB table to store group policy statement, and an Amazon Cognito user pool for managing federated user authentication.
AWS Identity and Access Management (IAM) and Amazon API Gateway to manage permissions and proxying egress requests from external clients.
Step 5
Amazon EventBridge for event-driven application messaging between micro-services and notifications for user.
Step 6
- AWS Lambda functions for handling API requests (NodeJS & Java), and deploy dynamic infrastructure for each data product (NodeJS).
- AWS Step Functions for managing the lifecycle of data products, and asynchronous life-cycle of query execution.
- Amazon Simple Storage Service (S3) buckets for storing processed data, user-defined scripts, and file uploads.
- AWS Glue tables and resources for handling the data extract, transform, and load (ETL) processing.
- Amazon Athena for performing federated queries which stores results in S3 buckets.
- DynamoDB data stores for saved queries, query history, and query caching, and governance metadata.
Step 7
- Lambda functions for handling source import.
- CloudFormation stack to manage resources.
- Step Functions for orchestrating lifecycle management.
- AWS Glue crawlers, data catalogues, and jobs for ETL.
- AWS Secrets Manager to store external credentials.
- Amazon Elastic Container Service (Amazon ECS) tasks for processing large data ingestion jobs.
- Athena and Amazon Comprehend for detecting personal identifiable information (PII) entities.
Step 8
Ingress (Data Connectors): This solution supports multiple source data connectors out-of-the-box including file upload, Amazon S3, Amazon Kinesis, Amazon CloudWatch, Google BigQuery, Google Cloud Storage, and Google Analytics, and databases such as MySql5, PostgreSQL, Oracle, and Microsoft SQL.
Step 9
Egress (Clients): This solution supports both The Java Database Connectivity (JDBC) and the Microsoft Open Database Connectivity (ODBC) standards for consuming data from common clients.
Step 1
The AWS CloudFormation template provisions the following infrastructure and services provided by the solution.
Step 2
Amazon CloudFront and AWS WAF for static website hosting distribution and protection. An Amazon DynamoDB table is used to manage and provide persistent notifications in the user interface.
Step 3
Federated Identity: An Amazon Cognito user pool manages federating and storing users from external identity providers (IDPs).
Step 4
A DynamoDB table to store group policy statement, and an Amazon Cognito user pool for managing federated user authentication.
AWS Identity and Access Management (IAM) and Amazon API Gateway to manage permissions and proxying egress requests from external clients.
Step 5
Amazon EventBridge for event-driven application messaging between micro-services and notifications for user.
Step 6
- AWS Lambda functions for handling API requests (NodeJS & Java), and deploy dynamic infrastructure for each data product (NodeJS).
- AWS Step Functions for managing the lifecycle of data products, and asynchronous life-cycle of query execution.
- Amazon Simple Storage Service (S3) buckets for storing processed data, user-defined scripts, and file uploads.
- AWS Glue tables and resources for handling the data extract, transform, and load (ETL) processing.
- Amazon Athena for performing federated queries which stores results in S3 buckets.
- DynamoDB data stores for saved queries, query history, and query caching, and governance metadata.
Step 7
- Lambda functions for handling source import.
- CloudFormation stack to manage resources.
- Step Functions for orchestrating lifecycle management.
- AWS Glue crawlers, data catalogues, and jobs for ETL.
- AWS Secrets Manager to store external credentials.
- Amazon Elastic Container Service (Amazon ECS) tasks for processing large data ingestion jobs.
- Athena and Amazon Comprehend for detecting personal identifiable information (PII) entities.
Step 8
Ingress (Data Connectors): This solution supports multiple source data connectors out-of-the-box including file upload, Amazon S3, Amazon Kinesis, Amazon CloudWatch, Google BigQuery, Google Cloud Storage, and Google Analytics, and databases such as MySql5, PostgreSQL, Oracle, and Microsoft SQL.
Step 9
Egress (Clients): This solution supports both The Java Database Connectivity (JDBC) and the Microsoft Open Database Connectivity (ODBC) standards for consuming data from common clients.
- Publish Date
Note: Before you launch the solution in the AWS Management Console, ensure that you meet the prerequisites in the implementation guide.
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