Zoom
to
Snowflake

Zoom Data Integration with Snowflake

With Portable, integrate Zoom data with your Snowflake warehouse in minutes. Access your communication platform data from Snowflake without having to manage cumbersome ETL scripts.

The Two Paths to Connect Zoom to Snowflake

There are two ways to sync data from Zoom into your data warehouse for analytics.

Method 1: Manually Developing a Custom Data Pipeline Yourself

Write code from scratch or use an open-source framework to build an integration between Zoom and Snowflake.

Method 2: Automating the ETL Process with a No-Code Solution

Leverage a pre-built connector from a cloud-hosted solution like Portable.

How to Create Value with Zoom Data

Teams connect Zoom to their data warehouse to build dashboards and generate value for their business. Let’s dig into the capabilities Zoom exposes via their API, outline insights you can build with the data, and summarize the most common analytics environments that teams are using to process their Zoom data.

Extract: What Data Can You Extract from the Zoom API?

Zoom is a communication platform used for video conferencing, audio communication, phone calls, and chat.

To help clients power downstream analytics, Zoom offers an application programming interface (API) for clients to extract data on business entities. Here are a few example entities you can extract from the API:

  • Accounts
  • Devices
  • Groups
  • Meetings
  • Reports
  • Roles
  • Users
  • Webinars
  • Workspaces

You can visit the Zoom API Documentation to explore the entire catalog of available API resources and the complete schema definition for each.

As you think about the data you will need for analytics, don’t forget that Portable offers no-code integrations to other similar applications.

Regardless of the SaaS solution you use, it’s important to find a communication platform with robust data available for analytics.

Load: Which Destinations Are Best for Your Zoom ETL Pipeline?

To turn raw data from Zoom into dashboards, most companies centralize information into a data warehouse or data lake. For Portable clients, the most common ETL pipelines are:

  1. Zoom to Snowflake Integration
  2. Zoom to Google BigQuery Integration
  3. Zoom to Amazon Redshift Integration
  4. Zoom to PostgreSQL Integration
Common Data Warehouses
Common Data Warehouses

Once you have a destination to load the data, it’s common to combine Zoom data with information from other enterprise applications like Jira, Mailchimp, HubSpot, Zendesk, and Klaviyo.

From there, you can build cross-functional dashboards in a visualization tool like Power BI, Tableau, Looker, or Retool.

Develop: Which Dashboards Should You Build with Zoom Data?

Now that you have identified the data you want to extract, the next step is to plan out the dashboards you can build with the data.

As a process, you want to consume raw data, overlay SQL logic, and build a dashboard to either 1) increase revenue or 2) decrease costs.

Replicating Zoom data into your cloud data warehouse can unlock a wide array of opportunities to power analytics, automate workflows, and develop products. The use cases are endless.

Now that we have a clear sense of the insights we can create, let’s compare the process of developing a custom Zoom integration with the benefits of using a no-code ETL solution like Portable.

Method 1: Building a Custom Zoom ETL Pipeline

To build your own Zoom integration, there are three steps:

  1. Navigate the Zoom API documentation
  2. Make your first API request
  3. Turn an API request into a complete data pipeline

Let’s walk through the process in more detail.

How to Interpret Zoom’s API Documentation

When reading API documentation, there are a handful of key concepts to consider.

Authentication

There are many common authentication mechanisms. OAuth 2.0 (Auth Code and Client Credentials), API Keys, JWT Tokens, Personal Access Tokens, Basic Authentication, etc. For Zoom, it’s important to identify the authentication mechanism and how best to incorporate the necessary credentials into your API requests.

Zoom must authenticate each HTTP request made to the Zoom API. Zoom supports OAuth 2.0.

Resources

It’s important to identify the Zoom API endpoints you want to use for analytics. Most APIs offer a combination of GET, POST, PUT, and DELETE request methods; however, for analytics, GET requests are typically the most useful. At times, POST requests can be used to extract data as well.

For Zoom, the zoom rooms endpoint is a great place to get started.

Request Parameters

For each API endpoint you would like to use for analytics, you need to understand the method (GET, POST, PUT, or DELETE) and the URL, but there are other considerations to take into account as well. You should look out for pagination mechanics, query parameters, and parameters that are added to the request path.

Zoom uses page_size and page_number parameters for pagination.

Some API endpoints require that the URL route contain unique identifiers from a prior API response.

For instance, you may require an roomId returned from another API in order to obtain specific room information.

How Do You Call the Zoom API? (Tutorial)

  1. Follow the instructions above to read the Zoom API documentation
  2. Identify and collect your credentials for authentication
  3. Pick the API resource you want to pull data from
  4. Configure the necessary parameters, method, and URL to make your first request (e.g. with curl or Postman)
  5. Add your credentials and make your first API call . Here is an example request using curl (without real credentials):
curl https://api.zoom.us/v2/rooms/{roomId} \
  -header 'Authorization: Basic {TOKEN}'  \
 --header 'Accept: application/json'

How Do You Maintain a Custom Zoom to Snowflake ETL Pipeline?

Making a call to the Zoom API is just the beginning of maintaining a complete custom ETL pipeline.

Here is a getting-started guide to building a production-grade pipeline for Zoom:

  • For each API endpoint, define schemas (which fields exist and the type for each)
  • Process the API response and parse the data (typically parsing JSON or XML)
  • Handle and replicate nested objects and custom fields
  • Identify which Zoom fields are primary keys and which keys are required vs. optional
  • Version control your changes in a git-based workflow (using GitHub, GitLab, etc.)
  • Handle code dependencies in your toolchain and the upgrades that come with each
  • Monitor the health of the upstream API, and —when things go wrong— troubleshoot via the status page, reach out to support, and open tickets
  • Handle error codes (HTTP error codes like 400s, 500s, etc.)
  • Manage and respect rate limits imposed by the server

We won’t go into detail on all of the items above, but rate limits are a great example of the complexity found in a production-grade data pipeline.

Light APIs limits: 30 requests/second for Pro Accounts and 80 requests/second for Business+ Accounts.

Medium APIs limits: 20 requests/second for Pro Accounts and 60 requests/second for Business+ Accounts.

Heavy APIs limits: 10 requests/second for Pro Accounts and 40 requests/second for Business+ Accounts.

Resource-intensive APIs limits: 10 requests/second for Pro Accounts and 20 requests/second for Business+ Accounts.

If you don’t respect rate limits, and if you can’t handle server responses (like 429 errors with a Retry-After header), your pipeline can break, and analytics can become out-of-date.

What Are the Drawbacks of Building the Zoom ETL Pipeline Yourself?

You can probably tell at this point that there is a lot of work that goes into building and maintaining an ETL pipeline from Zoom to your data warehouse.

If you want less development work, faster insights, and no ongoing responsibilities, you should consider a cloud-hosted ETL solution.

Let’s walk through the setup process for a no-code ETL solution and its benefits.

Method 2: Using a No-Code Zoom ETL Solution

No-code ETL solutions are simple. Vendors specialize in building and maintaining data pipelines on your behalf. Instead of starting from scratch for each integration. Companies like Portable create connector templates that can be leveraged by hundreds or thousands of clients.

Step-By-Step Tutorial for Configuring Your Zoom ETL Pipeline

Off-the-shelf ETL tools offer a no-code setup process. Here are the instructions to connect Zoom to your cloud data warehouse with Portable.

  1. Create an account (no credit card required)
  2. Add a source —search for and select Zoom
  3. Authenticate with Zoom using the instructions in the Portable console
  4. Select Snowflake and authenticate
  5. Set up a flow connecting Zoom to your analytics environment
  6. Run your flow to replicate data from Zoom to your warehouse
  7. Use the dropdown to set your data flow to run on a cadence

What Are the Benefits of Using Portable for Zoom ETL?

No-Code Simplicity

Start moving Zoom data in minutes. Save yourself the headaches of reading API documentation, writing code, and worrying about maintenance. Leave the hassle to us.

Easy to Understand Pricing

With predictable, fixed-cost pricing per data flow, you know exactly how much your Zoom integration will cost every month.

Fast Development Speeds

Access lightning-fast connector development. Portable can build new integrations on-demand in hours or days.

Hands-On Support

APIs change. Schemas evolve. Zoom will have maintenance issues and errors. With Portable, we will do everything in our power to make your life easier.

Unlimited Data Volumes

You can move as much data from Zoom to Snowflake as you want without worrying about usage credits or overages. Instead of analyzing your ETL costs, you should be analyzing your data.

Free to Get Started

Sign up and get started for free. You don’t need a credit card to manually trigger a data sync, so you can try all of our connectors before paying a dime.

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