Facet is an exploratory analytics platform that makes data analytics a team sport. Let the Facet team make a custom workspace on top of your BigQuery data, and see the power of Facet firsthand. All you need to get started are your BigQuery connection details.

Requirements

You'll want the following on hand to get started:

  • Dataset Name and Table Name you would like to visualize from your BigQuery
  • Service Account Key JSON file, with the following permissions:
    • BigQuery Data Viewer
    • BigQuery Job User

Need help? Check out the full guide to creating a BigQuery service account.

Service account creation in BigQueryService account creation in BigQuery

Service account creation in BigQuery

Sign Up

If you already have an account, you can skip this section

  • Navigate to our sign up page
  • Sign up with your Google account, or create an account with your email
    • If you log in using email, be sure to verify your email address via our confirmation email
  • Once logged in, ensure that you have your Company Name set up in Account Settings

📘

Account Settings > Company Name

Facet requires a verified email address (either via Google log-in or email verification) and a Company Account to create a workspace.

If a member of your company has already created your company account, you will be added to it automatically and will not have to create a new one. You can see your Account Settings here.

Add Connection Details

  • To get started, open the workspace dropdown, and click "+ Create New Workspace"
  • In the Create New Workspace flow:
    • Enter a Workspace Name and URL
    • Click Next
  • Click "+ Create New Database" to open the database creation panel:
    • Database Name (internal name, does not need to match database name in BigQuery)
    • Database Type, select BigQuery
    • Click the "+" button to upload new credentials — upload your BigQuery JSON Key File
  • Click Save and then Next
  • Click "+ Create New Dataset" to open the dataset creation panel:
    • Dataset Name (internal name, does not need to match dataset/table name in BigQuery)
    • BigQuery Dataset, dataset name in BigQuery
    • Table Name, table name in BigQuery
    • Timestamp Field, main timestamp column in your dataset
    • Minimum Granularity, granularity available in your timestamp
  • Click Save

Let us do the rest!

Reach out to your Facet account lead, and we'll get a flexible, robust analytics layer delivered to your desk within 24 hours. Some extra details that will help us fine-tune your workspace to be as useful as possible:

  • What are your top 5-10 metrics, and how do you define them? (e.g. is video completion rate VIDEO_COMPLETE/VIDEO_0 or VIDEO_COMPLETE/IMPRESSIONS)
  • What are common analytics questions that your team has to answer daily?
  • What are less common analytics questions that you currently find difficult to answer with your available dashboards?

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