aws-quicksight
Manage AWS QuickSight resources
TLDR
List datasets
List users
List groups
List dashboards
Display detailed information about a dataset
Display who has access to the dataset and what kind of actions they can perform on the dataset
SYNOPSIS
aws quicksight command [options]
PARAMETERS
command
Represents a specific QuickSight API operation to be performed. Examples include 'create-dashboard', 'list-users', 'update-data-set', etc. Each command has its own set of specific parameters.
options
These are parameters specific to the chosen QuickSight command. They define the details of the operation, such as '--dashboard-id', '--aws-account-id', '--name', '--definition', etc. Common options also include '--output' (e.g., json, text, table) and '--region'.
create-dashboard
Creates a new QuickSight dashboard with specified properties.
describe-dashboard
Retrieves detailed information about a specific QuickSight dashboard.
list-dashboards
Lists all QuickSight dashboards in the specified AWS account.
create-data-set
Creates a new QuickSight dataset, defining its schema and connection to a data source.
describe-data-set
Retrieves detailed information about a specific QuickSight dataset.
list-data-sets
Lists all QuickSight datasets in the specified AWS account.
create-data-source
Creates a new QuickSight data source connection (e.g., S3, Redshift, SQL Server).
list-data-sources
Lists all QuickSight data sources in the specified AWS account.
register-user
Registers a new user to access QuickSight within the account.
list-users
Lists all QuickSight users registered in the specified AWS account.
get-dashboard-embed-url
Generates a URL that can be used to embed a QuickSight dashboard into an application.
DESCRIPTION
The aws quicksight command is a sub-command of the AWS Command Line Interface (CLI), providing a programmatic interface to interact with Amazon QuickSight. QuickSight is a cloud-native business intelligence (BI) service that allows users to build visualizations, perform ad-hoc analysis, and get business insights from their data. The CLI integration enables automation of various QuickSight tasks, including managing users, groups, dashboards, analyses, datasets, data sources, themes, and templates. It's widely used for scripting, integrating with CI/CD pipelines, and automating QuickSight resource provisioning and management.
CAVEATS
1. AWS CLI Installation: The aws quicksight command requires the AWS CLI to be installed and properly configured with AWS credentials.
2. IAM Permissions: The AWS Identity and Access Management (IAM) user or role executing the command must have the necessary QuickSight permissions to perform the requested operation.
3. Region Specificity: QuickSight resources are region-specific. Ensure the AWS region is correctly configured or specified using the --region option.
4. API Limits: Be aware of QuickSight API rate limits when scripting extensive operations.
5. Output Paging: For commands that return a large number of results (e.g., list-dashboards), use --starting-token and --max-items for pagination.
AUTHENTICATION AND CONFIGURATION
Before using aws quicksight, ensure your AWS CLI is configured with valid AWS credentials (aws configure) that have the necessary IAM permissions for QuickSight operations. The CLI automatically picks up credentials from environment variables, shared credential files, or IAM roles.
COMMON GLOBAL OPTIONS
Many aws quicksight commands support global AWS CLI options like --output json|text|table to control the output format, and --query for JMESPath filtering of results. Using --output json with tools like jq is common for advanced processing.
HISTORY
Amazon QuickSight was first announced at AWS re:Invent in October 2015 and became generally available in November 2016. The aws quicksight CLI commands were subsequently integrated into the main AWS CLI tool, allowing developers and administrators to programmatically interact with the service. Its development has closely mirrored the evolution of QuickSight itself, with new commands and parameters added to support features like embedded analytics, ML insights, and enhanced data connectivity, reflecting its growing role as a key AWS BI service.