with Microsoft Power BI and Pinecone?
Emits a new event when a dataset refresh operation has completed. See the documentation
Emits an event when a dataset refresh operation has failed in Power BI. See the documentation
Emit new event when a new dataset refresh operation is created. See the documentation
Adds new data rows to the specified table within the specified dataset from My workspace. See the documentation
Deletes one or more vectors by ID, from a single namespace. See the documentation
Cancels a refresh operation for a specified dataset in Power BI. See the documentation
Looks up and returns vectors by ID, from a single namespace.. See the documentation
Creates a new Push Dataset in Power BI. See the documentation
The Microsoft Power BI API allows you to interact with your Power BI assets programmatically. With this API, you can embed your reports and dashboards into applications, manage Power BI datasets, push data into datasets for real-time dashboard updates, and automate your reporting workflows. On Pipedream, you can use this API to create intricate workflows that react to various triggers, like webhooks or schedules, and perform actions like refreshing datasets, posting to datasets, and managing Power BI assets.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
microsoft_power_bi: {
type: "app",
app: "microsoft_power_bi",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.powerbi.com/v1.0/myorg/availableFeatures`,
headers: {
Authorization: `Bearer ${this.microsoft_power_bi.$auth.oauth_access_token}`,
},
})
},
})
The Pinecone API enables you to work with vector databases, which are essential for building and scaling applications with AI features like recommendation systems, image recognition, and natural language processing. On Pipedream, you can create serverless workflows integrating Pinecone with other apps, automate data ingestion, query vector databases in response to events, and orchestrate complex data processing pipelines that leverage Pinecone's similarity search.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
pinecone: {
type: "app",
app: "pinecone",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.pinecone.io/collections`,
headers: {
"Api-Key": `${this.pinecone.$auth.api_key}`,
},
})
},
})