This Quick Start Guide (QSG) walks you through configuring Nexadata to extract extended audit log details from your Anaplan tenant, enrich the raw event codes with readable descriptions, and prepare the data for downstream audit analysis. Anaplan's native audit log records every user action as a numeric event code. Nexadata translates these codes into meaningful event messages and joins them with user, model, and workspace context, so you can answer compliance and activity questions without manual lookups.
Estimated time: ~36 minutes
🎯 What You'll Build
By the end of this QSG you'll have a Nexadata Workflow that produces a single enriched audit log dataset on every run. Each record includes:
Who: the Anaplan user (with INTERNAL_USER substituted for system events)
Where: the workspace and model the action affected
What: the action name (Imports, Exports, or Processes), pulled from the Stack Actions pipeline
What it means: a human-readable event message from the Activity Event Codes lookup
When: the event timestamp in clean ISO format
You can then schedule this Workflow to run on a cadence and feed the output into BI tools, exports, or alerting systems.
✅ Prerequisites
Before starting this QSG, confirm that two foundational connections are already in place. Both come from the introductory Anaplan QSG. If you haven't built them yet, complete just those two steps and return here.
Required (from the Anaplan QSG)
🔗 Step 1 - Create a Source Connection to Integrate with Anaplan. Establishes the source connection Nexadata uses to reach your Anaplan tenant.
🔗 Step 2 - Create an Anaplan Connection. Authenticates Nexadata against your Anaplan workspace so it can read audit data.
Recommended
For a broader view of how Nexadata supports Anaplan teams, we recommend the full introductory Anaplan QSG. It covers segment hierarchy automation and other Anaplan use cases:
In this QSG, you'll work through the following phases:
Phase 1 - Set up the data foundation
Step 1 - Create the Anaplan Audit Datasets: Build the nine Nexadata datasets that pull each Anaplan audit and administrative data source. (⏱ 10 min)
Step 2 - Create the Activity Event Codes Dataset: Build a lookup dataset that maps Anaplan audit event codes to readable event messages. (⏱ 3 min)
Step 3 - Tag the Anaplan Audit Datasets: Apply a shared "Audit Data" tag to every dataset that feeds the Anaplan audit log workflow. (⏱ 2 min)
Phase 2 - Create the Workflow
Step 4 - Create the Anaplan Audit Log Extraction Workflow: Create a new Workflow and add all tagged audit datasets so they're ready for transformation. (⏱ 3 min)
Phase 3 - Build the Pipelines
Step 5 - Build the Stack Actions Supporting Pipeline: Use AI Copilot to combine the Anaplan Imports, Exports, and Processes datasets into a single output dataset. (⏱ 5 min)
Step 6 - Build the Augment Events Supporting Pipeline: Use AI Copilot to join user, workspace, model, action, and audit code context to raw Anaplan events. (⏱ 6 min)
Step 7 - Build the Final Output Pipeline: Build the Output Pipeline that produces the final, schema-stable audit log dataset using AI Copilot and a sample CSV target. (⏱ 7 min)
Let's get started!