Particle to Google Data Studio

This page provides you with instructions on how to extract data from Particle and analyze it in Google Data Studio. (If the mechanics of extracting data from Particle seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

What is Particle?

Particle allows businesses to bring their Internet of Things (IoT) products to market faster. It provides a secure, easy-to-use, full-stack IoT cloud platform and low-cost connected hardware.

What is Google Data Studio?

Google Data Studio is a simple dashboard and reporting tool. It's free and easy to use, but it lacks the sophisticated features of higher-end reporting software. Many of the connectors it supports are for Google products, but third parties have written partner connectors to a wide variety of data sources. Its drag-and-drop report editor lets users create about 15 types of charts.

Getting data out of Particle

Particle exposes events through webhooks. To use webhooks, log into your Particle console and click on the Integrations tab, then click New Integration > Webhook. Set the event name to the item you want to track; it's good practice to specify the name of the field where you want the data to live in your data warehouse. Set the URL to the key or token that you'll use to accept the data. Leave the request type as POST. In the device field, select the device you want to trigger the webhook. Finally, click Create Webhook.

Sample Particle data

Particle sends data in JSON format via webhook through a POST request whenever an event triggers it to do so. The JSON fields and endpoints will match the data collected by your form. For instance:

{
    "event": [event-name],
    "data": [event-data],
    "published_at": [timestamp],
    "coreid": [device-id]
}

Loading data into Google Data Studio

Google Data Studio uses what it calls "connectors" to gain access to data. Data Studio comes bundled with 17 connectors, mostly to pull in data from other Google products. It also supports connectors to MySQL and PostgreSQL databases, and offers 200 connectors to other data sources built and supported by partners.

Using data in Google Data Studio

Google Data Studio provides a graphical canvas onto which users drag and drop datasets. Users can set dimensions and metrics, specify sorting and filtering, and tailor the way reports and charts are displayed.

Keeping Particle data up to date

Once you've coded up a script or written a program to get the data you want and move it into your data warehouse, you're going to have to maintain it. If Particle modifies its API, or sends a field with a datatype your code doesn't recognize, you may have to modify the script. If your users want slightly different information, you definitely will have to.

From Particle to your data warehouse: An easier solution

As mentioned earlier, the best practice for analyzing Particle data in Google Data Studio is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Particle to Redshift, Particle to BigQuery, Particle to Azure Synapse Analytics, Particle to PostgreSQL, Particle to Panoply, and Particle to Snowflake.

Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data automatically, making it easy to integrate Particle with Google Data Studio. With just a few clicks, Stitch starts extracting your Particle data, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Google Data Studio.