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.
Popular Datawaves and Go Actions#
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Overview of Datawaves#
The Datawaves API offers rich functionality for tracking and analyzing user interactions on websites and applications. With this API, you can capture events, analyze user behavior, and gain insights that drive decision-making for product enhancements and personalized user experiences. On Pipedream, you can harness these capabilities to create automated workflows that respond to data collected by Datawaves in real-time, integrate with other services, and streamline analytics processes.
Connect Datawaves#
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,
})
},
})
Overview of Go#
You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.
Connect Go#
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)
}