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Google Cloud Storage: Define Your Own Schema

Overview

The Google Cloud Storage (GCS) integration with Analytics is available for Enterprise customers only. If interested, please contact us. You are required to grant Analytics access to your GCS bucket that contains your data.

In order to perform the following steps, you must have administrative access within GCS.

If there are additional enrichments required, such as joining with user property tables or deriving custom user_ids, please contact us.

Instructions

Adding a Data Source In Analytics

  1. In Analytics, click the gear icon and select Project Settings. 

  2. Click the Data Sources tab.

  3. Select New Data Source.

     

  4. Select Connect via Data Warehouse or Lake
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  5. Select Google Cloud Storage as your data connection and Define your own schema and select Connect.
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  6. You should see this Google Cloud Storage Overview screen. Click Next.mceclip2.png

Connection Information

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  1. For Source Format, select the file format of the data in your GCS.
  2. For Bucket Name, enter the name of the GCS bucket that Analytics should connect to.
  3. For File Path, enter the file path corresponding to the data you want to use in Analytics.
  4. Click Next.

Grant Permissions

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  1.  Log into your Google Console account.
  2. Navigate to the bucket that contains your data.
  3. Click on the Permissions tab.
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  4. Cklick on Add.
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      1. Add integrations@indicative-988.iam.gserviceaccount.com to the New Members field
      2. Select the Storage Object Viewer role and click Save
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Event Modeling

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  1. Events Field - Input the name of the field that should be used to derive your Analytics event names.
  2. Timestamp - Input the name of the timestamp field that should be used for querying in Analytics.
  3. Click Next.

User Modeling

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For more information on User Identification (Aliasing), please refer to this article.

  1. If you choose to enable Aliasing:
    1. Unauthenticated ID - Input the field used to identify anonymous users. This is typically cookie-based.
    2. Authenticated ID - Input the field used to identify known users. This should be an internal ID that would never change for a user. We do not recommend using an email address as it is PII.
  2. I you choose to disable Aliasing, press Disabled:
    1. Unauthenticated ID - Enter the field used to identify your users. All users must have a value for this field.

  3.  Press Next.

Scheduling

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  1. Select the Schedule Interval to adjust the frequency at which new data is available in Analytics.
  2. Set the Schedule Time for when the data should be extracted from your BigQuery environment. It is critical that 100% of the data is available by this time to avoid loading partial data.
  3. Select Save.

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You're all set! A Solutions Engineer will begin working on your data and you will be notified via email when ready.

Advanced Settings

For additional advanced settings such as excluding certain events and properties, please refer to this page.

 

If you have any questions or concerns about the above Integration, please contact your Customer Support Manager, or email support@mparticle.com.

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