Data Master

Data Master gives you a unified view of every unique event name, attribute name and identity type tracked in an mParticle workspace, gives detailed insight into each of these data points, and lets you provide your own annotations.

Use Data Master to:

  • Track compliance with your data plan - spot data points which are duplicated, inconsistently named, etc.
  • Identify and eliminate unnecessary or redundant data points
  • Annotate your data to help other teams in your organization understand and utilize it

Capabilities

Data Master allows you to:

  • Browse and search through each event, user attribute and user identity type tracked in the workspace.
  • Drill down to any individual data point and view:

    • Details of all attribute names associated with any event
    • The environments the event has been seen for — development (DEV), or production (PROD).
    • Which platforms the event has been for, and when the event was last seen for each platform.
  • Annotate any data point with descriptions, links to additional documentation, and alternate names.
  • View statistics on how many times the event was received and how many times it was forwarded to each output.

List view

The Data Master list view will display up to six main categories:

  • Custom Events
  • Screen Views
  • Commerce
  • User Information
  • Application Lifecycle
  • Consent

Data Master will only show a category heading if there is at least one matching data point to display.

Click on any data point to see detailed information. You can also add a description directly from the list view.

Search and Filter

If you’re looking for a specific set of data points, you can filter the list view by:

  • Search — show only data points with a name, description or other name containing a given substring.
  • Input/App Version — show only data points that have been seen for the selected inputs/app versions.
  • Environment — show only data points that have been seen in the dev or prod environments.
  • Channel — show only data points that have been seen for a selected channel. Channel is distinct from input and describes how a data point arrived at mParticle. For example, a data point may arrive for the iOS input from the SDK channel, via the Server to Server API channel, or from a Feed that can act as the iOS platform.
  • Date Range — show only data points that have been seen within a selected date range.

If you set multiple filters, only data points that match all conditions will be displayed. Setting a filter will also clear any current category selection.

Details view

The details view gives you high-level detail on an individual data point, including the environments the event has been captured for, and when the event was last seen for each platform.

Users with admin access can annotate data points in the following ways:

  • Tags - a list of custom categories the data point belongs to.
  • External Link - a link to your wiki or any other resource containing documentation about the data point
  • Description - a custom text field where you can describe the data point, expected attributes, how it’s used, and any other relevant information.
  • Additional Names - a list of alternate names the data point is known by. For example, legacy names or names from a partner feed.

For events, the details view also shows every attribute name that has ever been associated with the event. For each input and channel the attribute has been captured for, you can see the total volume of attributes received in the last 30 days, when the attribute was last seen, and the data type. The data type of a new attribute initially defaults to string but is updated automatically by mParticle as you capture more data. Possible data types are:

  • String
  • Number
  • Boolean
  • Date

Stats view

For events, the stats view shows two important groups of statistics for a selected date:

  • Input stats show how many instances of the event have been received, by platform and channel.
  • Output stats show the number of messages sent to each outputs based on the event, as well as the delta between the number of events received and outgoing messages sent. This delta can be useful for troubleshooting, but note that a difference between volume sent and received usually doesn’t indicate a problem. Expansion of eCommerce events can cause multiple messages to be sent to an output for a single event. Likewise, filtering or an output partners minimum requirements can cause mParticle not to forward every event we receive.

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