Datawaves

Customer-Facing Analytics

Integrate the Datawaves API with the Go API

Setup the Datawaves API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Datawaves and Go remarkably fast. Free for developers.

Run Go Code with the Go API

Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.

 
Try it

Overview of Datawaves

Datawaves is a powerful API that enables developers to easily and efficiently
access data from a variety of sources. With Datawaves, you can easily connect
to and query data from popular data sources such as Amazon Redshift, Google
BigQuery, and Microsoft SQL Server.

In addition, Datawaves provides a number of features that make it easy to work
with data, including:

  • Query Builder: A powerful query builder that makes it easy to construct
    complex queries.
  • Data Explorer: A visual interface that makes it easy to explore and analyze
    data.
  • Support for popular data formats: Datawaves supports CSV, JSON, and XML.
  • Integration with popular programming languages: Datawaves offers native
    integrations with popular programming languages such as Java, Python, and
    Node.js.

Connect Datawaves

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    datawaves: {
      type: "app",
      app: "datawaves",
    }
  },
  async run({steps, $}) {
    const data = {
      "id": `123`,
      "product": `iPhone Charger`,
    }
    return await axios($, {
      method: "post",
      url: `https://datawaves.io/api/v1.0/projects/${this.datawaves.$auth.project_id}/events/test`,
      headers: {
        "Authorization": `${this.datawaves.$auth.secret_key}`,
      },
      data,
    })
  },
})

Connect Go

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package main

import (
	"fmt"

	pd "github.com/PipedreamHQ/pipedream-go"
)

func main() {
	// Access previous step data using pd.Steps
	fmt.Println(pd.Steps)

	// Export data using pd.Export
	data := make(map[string]interface{})
	data["name"] = "Luke"
	pd.Export("data", data)
}