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---
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title: Run QuickSight Connector using the CLI
slug: /connectors/dashboard/quicksight/cli
---
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# Run QuickSight using the metadata CLI
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| Stage | PROD |
|------------|------------------------------|
| Dashboards | {% icon iconName="check" /%} |
| Charts | {% icon iconName="check" /%} |
| Owners | {% icon iconName="cross" /%} |
| Tags | {% icon iconName="cross" /%} |
| Datamodels | {% icon iconName="cross" /%} |
| Lineage | {% icon iconName="check" /%} |
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In this section, we provide guides and references to use the QuickSight connector.
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Configure and schedule QuickSight metadata and profiler workflows from the OpenMetadata UI:
- [Requirements](#requirements)
- [Metadata Ingestion](#metadata-ingestion)
## Requirements
{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%}
To deploy OpenMetadata, check the Deployment guides.
{%/inlineCallout%}
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AWS QuickSight Permissions
To execute metadata extraction and usage workflow successfully the IAM User should have enough access to fetch required data. Following table describes the minimum required permissions
| # | AWS QuickSight Permission |
| :---------- | :---------- |
| 1 | DescribeDashboard |
| 2 | ListAnalyses |
| 3 | ListDataSources |
| 4 | ListDashboards |
| 5 | DescribeAnalysis |
| 6 | DescribeDataSet |
| 7 | ListDataSets |
| 8 | DescribeDataSource |
Here is how to add Permissions to an IAM user.
- Navigate to the IAM console in the AWS Management Console.
- Choose the IAM user or group to which you want to attach the policy, and click on the "Permissions" tab.
- Click on the "Add permissions" button and select "Attach existing policies directly".
- Search for the policy by name or by filtering the available policies, and select the one you want to attach.
- Review the policy and click on "Add permissions" to complete the process.
```json
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"quicksight:DescribeDashboard",
"quicksight:ListAnalyses",
"quicksight:ListDataSources",
"quicksight:ListDashboards",
"quicksight:DescribeAnalysis",
"quicksight:DescribeDataSet",
"quicksight:ListDataSets",
"quicksight:DescribeDataSource"
],
"Resource": "*"
}
]
}
```
To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
custom Airflow plugins to handle the workflow deployment.
### Python Requirements
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To run the QuickSight ingestion, you will need to install:
```bash
pip3 install "openmetadata-ingestion[quicksight]"
```
## Metadata Ingestion
All connectors are defined as JSON Schemas.
[Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/dashboard/quickSightConnection.json)
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you can find the structure to create a connection to QuickSight.
In order to create and run a Metadata Ingestion workflow, we will follow
the steps to create a YAML configuration able to connect to the source,
process the Entities if needed, and reach the OpenMetadata server.
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The workflow is QuickSightled around the following
[JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json)
### 1. Define the YAML Config
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This is a sample config for QuickSight:
{% codePreview %}
{% codeInfoContainer %}
#### Source Configuration - Service Connection
{% codeInfo srNumber=1 %}
**awsConfig**
- **AWS Access Key ID**: Enter your secure access key ID for your Glue connection. The specified key ID should be authorized to read all databases you want to include in the metadata ingestion workflow.
- **AWS Secret Access Key**: Enter the Secret Access Key (the passcode key pair to the key ID from above).
- **AWS Region**: Enter the location of the amazon cluster that your data and account are associated with.
- **AWS Session Token (optional)**: The AWS session token is an optional parameter. If you want, enter the details of your temporary session token.
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- **Endpoint URL (optional)**: Your Glue connector will automatically determine the AWS QuickSight endpoint URL based on the region. You may override this behavior by entering a value to the endpoint URL.
{% /codeInfo %}
{% codeInfo srNumber=2 %}
**awsAccountId**: AWS Account ID
{% /codeInfo %}
{% codeInfo srNumber=3 %}
**identityType**: The authentication method that the user uses to sign in.
{% /codeInfo %}
{% codeInfo srNumber=4 %}
**namespace**: The Amazon QuickSight namespace that contains the dashboard IDs in this request ( To be provided when identityType is `ANONYMOUS` )
{% /codeInfo %}
#### Source Configuration - Source Config
{% codeInfo srNumber=5 %}
The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/dashboardServiceMetadataPipeline.json):
- **dbServiceNames**: Database Service Names for ingesting lineage if the source supports it.
- **dashboardFilterPattern**, **chartFilterPattern**, **dataModelFilterPattern**: Note that all of them support regex as include or exclude. E.g., "My dashboard, My dash.*, .*Dashboard".
- **includeOwners**: Set the 'Include Owners' toggle to control whether to include owners to the ingested entity if the owner email matches with a user stored in the OM server as part of metadata ingestion. If the ingested entity already exists and has an owner, the owner will not be overwritten.
- **includeTags**: Set the 'Include Tags' toggle to control whether to include tags in metadata ingestion.
- **includeDataModels**: Set the 'Include Data Models' toggle to control whether to include tags as part of metadata ingestion.
- **markDeletedDashboards**: Set the 'Mark Deleted Dashboards' toggle to flag dashboards as soft-deleted if they are not present anymore in the source system.
{% /codeInfo %}
#### Sink Configuration
{% codeInfo srNumber=6 %}
To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.
{% /codeInfo %}
{% partial file="workflow-config.md" /%}
{% /codeInfoContainer %}
{% codeBlock fileName="filename.yaml" %}
```yaml
source:
type: quicksight
serviceName: local_quicksight
serviceConnection:
config:
type: QuickSight
```
```yaml {% srNumber=1 %}
awsConfig:
awsAccessKeyId: KEY
awsSecretAccessKey: SECRET
awsRegion: us-east-2
awsSessionToken: Token
```
```yaml {% srNumber=2 %}
awsAccountId: <aws-account-id>
```
```yaml {% srNumber=3 %}
identityType: IAM #QUICKSIGHT, ANONYMOUS
```
```yaml {% srNumber=4 %}
namespace: #to be provided if identityType is Anonymous
```
```yaml {% srNumber=5 %}
sourceConfig:
config:
type: DashboardMetadata
markDeletedDashboards: True
# dbServiceNames:
# - service1
# - service2
# dashboardFilterPattern:
# includes:
# - dashboard1
# - dashboard2
# excludes:
# - dashboard3
# - dashboard4
# chartFilterPattern:
# includes:
# - chart1
# - chart2
# excludes:
# - chart3
# - chart4
```yaml {% srNumber=6 %}
sink:
type: metadata-rest
config: {}
```
{% partial file="workflow-config-yaml.md" /%}
{% /codeBlock %}
{% /codePreview %}
### 2. Run with the CLI
First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
```bash
metadata ingest -c <path-to-yaml>
```
Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration,
you will be able to extract metadata from different sources.