Triggered Unfold
Infoveave Data Automation — Pivot & Transpose
Multiple event rows for the same session become one clean, structured record — identified by the trigger and ready for direct analysis.
Event logs, machine sensor streams, and session-based monitoring systems frequently store data as a sequence of rows per session — one row marking the session start or trigger event, followed by subsequent data rows with the actual readings or actions. This long-format log structure is difficult to analyze directly: filtering by session type, comparing sessions to each other, and aggregating across sessions requires first reconstructing individual sessions from the row stream. Triggered Unfold collapses these session-based row sequences into one structured record per session, using a specified trigger value to identify session boundaries and promoting subsequent data rows as properties on that session record. The result is a flat, wide-format table where each session is a single row ready for direct reporting, aggregation, and analysis.
What Triggered Unfold does
Collapse session or event-style rows into one structured record per session using a trigger value in Infoveave. Flatten log-format event streams into analyzable wide-format session records without code.
Part of Infoveave Data Automation on the Unified Data Platform.
When to use Triggered Unfold
- Your data is in a long-format event log where each session has a trigger row — such as a START or INIT event — followed by data rows, and you need one flat record per session
- You are processing sensor or machine readings stored as a sequence of rows per measurement session where the first row defines the session type and subsequent rows hold the data payload
- You want to flatten event stream data — such as call center interaction logs, IoT device sessions, or user journey events — into analyzable records without writing custom grouping and pivot logic
- You need to calculate session-level metrics such as duration, sequence count, or data values, but the raw data is stored across multiple rows that must first be collapsed into one row per session
When to avoid it
- Your data is already in a wide format with one row per session — no collapsing is needed
- The row sequences do not have a clear trigger or boundary marker — use Group by transformations to aggregate across rows without session boundary detection
- You want to go the other direction and expand one row into multiple rows — use Fold Multiple Columns or Fold an Array for that case
Where it fits in your Infoveave automation
Triggered Unfold is one step inside a multi-step Infoveave workflow. Chain it with other activities — no code, no manual hand-offs.
Build this workflow visually in Infoveave Data Automation — drag, connect, and schedule with no infrastructure setup.
How teams use Triggered Unfold
Real scenarios where this transformation saves hours of manual work.
Flatten Machine Test Session Logs into One Record per Test
A manufacturing quality team processes machine test logs where each test session appears as multiple rows in the data — a START row containing the session ID and test type, followed by DATA rows containing individual sensor readings. Triggered Unfold identifies each START row as the session trigger, collapses the subsequent DATA rows into properties on that session record, and produces one flat row per test session. The team can then filter tests by type, compare readings across sessions, and flag tests that exceeded tolerance thresholds — analysis that was impossible with the raw row-per-event log format.
Reconstruct Patient Visit Sessions from EHR Event Streams
A healthcare analytics team processes an electronic health record event stream where each patient visit appears as a sequence of rows — an ADMIT trigger row followed by procedure and observation data rows. Triggered Unfold collapses each patient visit into one structured record per admission using the ADMIT trigger, making it possible to compare visit types, calculate visit length, and report on procedure combinations without manual grouping and pivot logic in SQL.
Collapse User Session Events from Web Analytics Logs
A product analytics team processes web logging data where each user session is a sequence of rows — a SESSION_START row followed by page view and interaction data rows. Triggered Unfold uses SESSION_START as the trigger to identify session boundaries and collapses each session's subsequent rows into a single structured session record. The team can then analyze session depth, content engagement, funnel progression, and conversion by session type.
See Triggered Unfold in action
Input data (left) is transformed using the configuration below. The output table (right) is ready for dashboards or downstream steps.
SessionIDEventTypeSTARTEventDataInput Data
| SessionID | EventType | EventData |
|---|---|---|
| 1 | START | TypeA |
| 1 | DATA | Value1 |
| 1 | DATA | Value2 |
| 2 | START | TypeB |
| 2 | DATA | Value3 |
| 3 | START | TypeA |
| 3 | DATA | Value4 |
| 3 | DATA | Value5 |
| 3 | DATA | Value6 |
Output Data
| SessionID | START_EventData | DATA_EventData_1 | DATA_EventData_2 | DATA_EventData_3 |
|---|---|---|---|---|
| 1 | TypeA | Value1 | Value2 | |
| 2 | TypeB | Value3 | ||
| 3 | TypeA | Value4 | Value5 | Value6 |
Configuration
Key fields to configure in the Infoveave workflow builder. Full reference available in the documentation.
Key Column
Select the column that identifies which rows belong to the same session. All rows with the same key value — such as the same SessionID — are treated as one group. Triggered Unfold produces one output row per unique key value, collapsing all rows in the group into that single structured record.
Fold Column
Select the column that contains the event type or category values used to classify each row within a session group. The trigger value is looked for within this column. Once the trigger row is found, subsequent rows in the same group provide the session data.
Trigger Value
Specify the value in the Fold Column that identifies the trigger row — the session boundary marker. Rows where the Fold Column equals the trigger value mark the start of a session group and their data is promoted to session-level properties. Rows that follow the trigger row within the same key group become sequential data properties on the session record.
Data Column
Select the column that holds the data payload for each row — the values to carry forward into the structured session record. The trigger row's data value and each subsequent data row's value are all brought into the output record as named properties.
Frequently asked questions
Everything you need to know about Triggered Unfold in Infoveave.
Also in Pivot & Transpose — and what runs before & after
Transformations in the same family as Triggered Unfold, often chained together in the same Infoveave workflow.
Part of Infoveave Data Automation
80+ transformations. Zero manual steps.
Triggered Unfold is one of over 80 transformation activities available inside Infoveave workflows. Chain transformations together — no code, no exports, no waiting for IT.
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