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title	slug
Run PowerBI Connector using the CLI	/connectors/dashboard/powerbi/cli

Run PowerBI using the metadata CLI

In this section, we provide guides and references to use the PowerBI connector.

Configure and schedule PowerBI metadata and profiler workflows from the OpenMetadata UI:

Requirements
Metadata Ingestion

Requirements

To deploy OpenMetadata, check the Deployment guides.

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:

pip3 install "openmetadata-ingestion[powerbi]"

Metadata Ingestion

All connectors are defined as JSON Schemas. Here 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

1. Define the YAML Config

This is a sample config for PowerBI:

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)
      type: PowerBI
  sourceConfig:
    config:
      type: DashboardMetadata
      # 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
  openMetadataServerConfig:
    hostPort: <OpenMetadata host and port>
    authProvider: <OpenMetadata auth provider>

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

Source Configuration - Source Config

The sourceConfig is defined here:

dbServiceName: Database Service Name for the creation of lineage, if the source supports it.
dashboardFilterPattern and chartFilterPattern: Note that the dashboardFilterPattern and chartFilterPattern both support regex as include or exclude. E.g.,

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:

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: openmetadata
    securityConfig:
      jwtToken: '{bot_jwt_token}'

We support different security providers. You can find their definitions here. You can find the different implementation of the ingestion below.

Openmetadata JWT Auth

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: openmetadata
    securityConfig:
      jwtToken: '{bot_jwt_token}'

Auth0 SSO

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: auth0
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'

Azure SSO

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

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: custom-oidc
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'

Google SSO

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: google
    securityConfig:
      secretKey: '{path-to-json-creds}'

Okta SSO

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

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

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: custom-oidc
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'

KeyCloak SSO