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---
title: Run PowerBI Connector using the CLI
slug: /connectors/dashboard/powerbi/cli
---
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# Run PowerBI using the metadata CLI
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In this section, we provide guides and references to use the PowerBI connector.
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Configure and schedule PowerBI metadata and profiler workflows from the OpenMetadata UI:
- [Requirements](#requirements)
- [Metadata Ingestion](#metadata-ingestion)
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## Requirements
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<InlineCallout color="violet-70" icon="description" bold="OpenMetadata 0.12 or later" href="/deployment">
To deploy OpenMetadata, check the <a href="/deployment">Deployment</a> guides.
</InlineCallout>
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
To run the PowerBI ingestion, you will need to install:
```bash
pip3 install "openmetadata-ingestion[powerbi]"
```
## 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/powerBIConnection.json)
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you can find the structure to create a connection to PowerBI.
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.
The workflow is modeled around the following
[JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json)
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### 1. Define the YAML Config
This is a sample config for PowerBI:
```yaml
source:
type: powerbi
serviceName: local_powerbi
serviceConnection:
config:
clientId: clientId
clientSecret: secret
tenantId: tenant
# scope:
# - https://analysis.windows.net/powerbi/api/.default (default)
# authorityURI: https://login.microsoftonline.com/ (default)
# hostPort: https://analysis.windows.net/powerbi (default)
# pagination_entity_per_page: 100 (default)
# useAdminApis: true or false
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type: PowerBI
sourceConfig:
config:
type: DashboardMetadata
overrideOwner: True
markDeletedDashboards: True
includeTags: True
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# dbServiceNames:
# - service1
# - service2
# dashboardFilterPattern:
# includes:
# - dashboard1
# - dashboard2
# excludes:
# - dashboard3
# - dashboard4
# chartFilterPattern:
# includes:
# - chart1
# - chart2
# excludes:
# - chart3
# - chart4
sink:
type: metadata-rest
config: {}
workflowConfig:
# loggerLevel: DEBUG # DEBUG, INFO, WARN or ERROR
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openMetadataServerConfig:
hostPort: <OpenMetadata host and port>
authProvider: <OpenMetadata auth provider>
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```
#### Source Configuration - Service Connection
- **hostPort**: URL to the PowerBI instance.
- **clientId**: PowerBI Client ID.
- **clientSecret**: PowerBI Client Secret.
- **tenantId**: PowerBI Tenant ID.
- **authorityUri**: Authority URI for the service.
- **scope**: Service scope. By default `["https://analysis.windows.net/powerbi/api/.default"]`.
- **Pagination Entity Per Page**: Entity Limit set here will be used to paginate the PowerBi APIs. PowerBi API do not allow more than 100 workspaces to be inputed at a time. This field sets the limit of entities used for paginating the powerbi APIs. By default 100
- **Use PowerBI Admin APIs**:
Option for using the PowerBI admin APIs:
1. Enabled (Use PowerBI Admin APIs):
Using the admin APIs will fetch the dashboard and chart metadata from all the workspaces available in the powerbi instance
2. Disabled (Use Non-Admin PowerBI APIs):
Using the non-admin APIs will only fetch the dashboard and chart metadata from the workspaces that have the security group of the service principal assigned to them.
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#### Source Configuration - Source Config
The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/dashboardServiceMetadataPipeline.json):
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- `dbServiceNames`: Database Service Name for the creation of lineage, if the source supports it.
- `dashboardFilterPattern` / `chartFilterPattern`: Note that all of them support regex as include or exclude. E.g., "My dashboard, My dash.*, .*Dashboard".
- `includeTags`: Set the 'Include Tags' 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.
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```yaml
dashboardFilterPattern:
includes:
- users
- type_test
```
#### Sink Configuration
To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.
#### Workflow Configuration
The main property here is the `openMetadataServerConfig`, where you can define the host and security provider of your OpenMetadata installation.
For a simple, local installation using our docker containers, this looks like:
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: openmetadata
securityConfig:
jwtToken: '{bot_jwt_token}'
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```
We support different security providers. You can find their definitions [here](https://github.com/open-metadata/OpenMetadata/tree/main/openmetadata-spec/src/main/resources/json/schema/security/client).
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You can find the different implementation of the ingestion below.
<Collapse title="Configure SSO in the Ingestion Workflows">
### Openmetadata JWT Auth
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: openmetadata
securityConfig:
jwtToken: '{bot_jwt_token}'
```
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### Auth0 SSO
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: auth0
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
```
### Azure SSO
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: azure
securityConfig:
clientSecret: '{your_client_secret}'
authority: '{your_authority_url}'
clientId: '{your_client_id}'
scopes:
- your_scopes
```
### Custom OIDC SSO
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: custom-oidc
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
```
### Google SSO
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: google
securityConfig:
secretKey: '{path-to-json-creds}'
```
### Okta SSO
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: http://localhost:8585/api
authProvider: okta
securityConfig:
clientId: "{CLIENT_ID - SPA APP}"
orgURL: "{ISSUER_URL}/v1/token"
privateKey: "{public/private keypair}"
email: "{email}"
scopes:
- token
```
### Amazon Cognito SSO
The ingestion can be configured by [Enabling JWT Tokens](https://docs.open-metadata.org/deployment/security/enable-jwt-tokens)
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: auth0
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
```
### OneLogin SSO
Which uses Custom OIDC for the ingestion
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: custom-oidc
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
```
### KeyCloak SSO
Which uses Custom OIDC for the ingestion
```yaml
workflowConfig:
openMetadataServerConfig:
hostPort: 'http://localhost:8585/api'
authProvider: custom-oidc
securityConfig:
clientId: '{your_client_id}'
secretKey: '{your_client_secret}'
domain: '{your_domain}'
```
</Collapse>
### 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.