The tracked data page is used to view summary information for tracked data:
Here, you can search for an entity value to access available tracked data summaries, and then choose to view summary details.
Tracked data summaries are available for data tracked via the track data shape, and for data tracked via connector endpoint field tags).
Data for the tracked data page is updated every 10 minutes (i.e. every 10 minutes the database is checked for new tracked items and these are pushed to the dashboard UI).
The tracked data page shows a maximum of 15 entries for any given tracked entity. So if you're tracking the same entity in more than 15 places, only the latest 15 entries are shown.
Tracked data summaries remain available for 15 days, starting from when an entity was last tracked. For example, if you're tracking customer IDs and ID 0100001 was tracked 14 days ago but then again today, it will be visible for another 15 days (and so on until it's not seen for 15 days).
Times shown on tracked data summaries are UTC.
To access the tracked data page, select process flows | tracked data from the left-hand navigation menu:
To find tracked data information for a particular field value, start by selecting the associated entity type - for example:
The entity type list includes all entity types that have been tracked (via the track data shape or via tagged endpoints).
Next, enter the value that you want to to review - for example, if you are tracking customer IDs, you'd enter the required customer ID here:
Tracked data summaries are displayed for the most recent process flow runs where this entity was tracked - for example:
As you type a value, the search updates instantly so you may notice that the list of available summaries changes as you type.
From here, you can click any summary to view details:
Each tracked data summary shows tracking information for the given entity in a flow run - for example:
You'll see one entry for each occasion that this entity was tracked in this run. In our example we have two entries because the associated process flow includes two track data shapes, and this entity passed through both.
Summary information varies slightly, depending on whether the data was tracked via a track data shape, or via tagged endpoints:
| Information | Track data shape | Tracked fields |
|---|---|---|
Receive / send
The flow direction for the associated tracked data, as defined in the track data shape.
The flow direction for the associated tracked data, as defined for the associated connector endpoint.
Date & time
The date & time that this data was tracked.
The date & time that this data was tracked.
Success / fail
If success criteria filters are defined in the track data shape, the success/failure marker is determined by the outcome of these.
If success criteria filters are NOT defined in the track data shape, the default marker is success.
Defaults to success for all tracked data.
Message
If a success criteria message is defined in the track data shape, it is shown here.
N/A
The track data shape is used to track processed data, based on field paths that you define. When data passes through a track data shape, the values associated with your defined field paths are tracked - which means they can be .
For example, you might want to track all customer_id values that pass through a flow, so at any time you can quickly check if/when/how a given customer record has been processed.
Tracked data shape is for 15 days after it was last tracked.
Depending on data volumes, allow 10 minutes for tracked data to be visible in data pools.
The track data shape works with incoming payloads from a , a , an , or a .
, , and variables are supported when defining success messages.
JSON payloads are supported.
You can add as many track data shapes to a process flow as required. For example, you might place one immediately after a receiving connector to track everything received before anything else happens to the data, and another after the final sending connector to track everything sent into your destination system.
To add and configure a new track shape, follow the steps below.
Step 1 In your process flow, add the track data shape in the usual way:
Step 2 Configure the settings as required - the table below summarises available fields:
Step 3 Save your settings., then access them again:
...you'll now see success criteria options at the bottom of the shape settings drawer:
Step 4 The success criteria options are optional. If you don't need to apply these then your setup is complete - close the settings drawer and continue with your process flow as required. If you do want to use these options, see below for guidance.
When data passes through a track data shape, specified data fields are tracked and by default, tracked data is marked as a success.
However, there may be times where you want to control the conditions under which the status of tracked data is deemed a success or a failure, and to record this outcome for future reference. The success criteria section allows you to:
When tracked data is marked as failed, it is still tracked and the shape still processes successfully - for example:
In this run log, notice that tracked data is marked as a failure (1) but tracked data is stored (2) and the track data step succeeds (3).
Any conditions that you want to apply can be added via filters. To define a new filter, click the add filter button:
You can add as many filters as you need - multiple filters work together with an 'AND' operator. Remember that you're defining conditions that must be met for a success outcome - if multiple filters are present they must ALL be matched. If one or more filters are not matched, the associated tracked data is marked as a failure.
Filters can be based on any field(s) found in your data, irrespective of whether you chosen to track them.
No success criteria filters are defined
Success criteria filters are defined and the outcome is success
Success criteria filters are defined and the outcome is failure
| Field | Summary |
|---|
Define filter conditions that must be met for an entity's progress to be reported as a success or failure in for this tracked item.
Add a message to be displayed in for this tracked item.
In this context, tracked data marked as a 'failure' simply means that one or more filters defined for success were not matched and therefore this item is reported as a failure in associated .
These filters work in the same way as in the dashboard - select/define a field, then set conditions and values.
The success or failure outcome from these filters is reported in the logs, and also in - for example:
You can define a message to be displayed in the for associated tracked data:
This message can be text-only, or any combination of text, , , and . For example:
In , this example is shown as:
Messages are added to when:
Source instance Source endpoint |
Entity |
Direction |
|
Field paths | Define one or more data fields to be tracked - i.e. fields that you may want to look up in the event of a query. |
If data is coming into the process flow via a , use these dropdown fields to select appropriate source connector details (i.e. the same instance and endpoint as configured for the previous connector shape). If data is coming into the flow via a non-connector source (such as a , , or ) then leave these fields blank.
If data is coming into the flow via a , this field will be set as required by default. Otherwise, select the entity type associated with the data field(s) that you want to track.
Note that the selection made here has no impact on how the shape performs - it simply determines how the tracked field is categorised in .
If data is received via a , this field will be set as required by default. Otherwise, select the flow direction (send or receive) associated with the data field(s) that you want to track:
Note that the selection made here has no impact on how the shape performs - it simply determines how the tracked field is categorised in .
If multiple fields are specified, these values are tracked as one, concatenated value. To track multiple fields separately, use one shape per field.
If data is received via a , you can navigate the associated data structure to select a field for tracking - for example: If data is received via a non-connector source (such as a , , or ), enter a path to the required field manually - for example:
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