Automating Flat File Uploads to Anaplan Data Orchestrator (ADO) – Best Practices and Methods

JorgePalma

Hello Anaplan Community,

I am seeking guidance on the most effective ways to automatically upload flat files to Anaplan Data Orchestrator (ADO).

Currently, our process involves loading flat files to an Anaplan Datahub using Anaplan APIs and custom Python scripting. With Anaplan Data Orchestrator's capabilities for data management and integration, we are exploring how to transition or enhance our existing workflows to leverage ADO for these automated file uploads.

My primary questions are:

• What are the recommended methods for programmatically or automatically uploading flat files (e.g., CSVs) directly to Anaplan Data Orchestrator?
• Are there specific Anaplan APIs, Anaplan Connect features, or ADO-native functionalities that support this kind of automation beyond manual file uploads?
• Given our current use of Python and Anaplan APIs for Datahub uploads, what would be the best practice for integrating these existing workflows with ADO for automated file ingestion?
• Are there any known considerations or common issues, such as time setting errors, or limitations regarding file formats or size, when setting up automated file uploads to ADO?

Any insights, examples, or pointers to relevant documentation would be greatly appreciated.

Thank you in advance for your help!

Dheeraj09

Great question — many teams transitioning to Anaplan Data Orchestrator (ADO) are exploring exactly this!

Since you're already using Anaplan APIs and Python for automated flat file uploads to a Data Hub, you’re in a good position to extend or transition this workflow to leverage ADO. Below are detailed answers to your key points:

1. Recommended Methods for Uploading Flat Files to ADO

As of now, ADO does not natively handle direct file uploads (e.g., CSVs) to Anaplan models. Instead, ADO orchestrates Anaplan actions (imports/exports/processes) and integrates with external systems via Anaplan Connect, APIs, or external connectors (e.g., Informatica, MuleSoft, SnapLogic).

For flat file ingestion, the best practice is:

• Continue uploading your flat files to the Anaplan Data Hub via API or Anaplan Connect
• Then use ADO to orchestrate imports from the Data Hub into spoke models

2. Programmatic Automation Options

Here are a few approaches for file upload automation:

a. Anaplan REST API + ADO

• Continue using the Anaplan REST API (v2.0) to upload your CSVs into the Data Hub.
• Then trigger ADO flows that:
  • Execute imports into spoke models
  • Run downstream processes or actions

b. Anaplan Connect + ADO

• Schedule Anaplan Connect scripts via a scheduler (e.g., Windows Task Scheduler or Cron)
• Follow this up with ADO flow executions as part of your orchestrated pipeline

c. External Orchestrators + ADO

• Tools like Apache Airflow, Azure Data Factory, or AWS Lambda (if you're on cloud infra) can be used to automate uploads and trigger ADO flows via Anaplan Transactional API or Integration API

💡 3. Integrating Your Python Workflows with ADO

Since you're already using Python and Anaplan APIs, you can do the following:

• Continue uploading files to the Data Hub model
• Add an HTTP request in Python to trigger the ADO Flow via:
  • Anaplan Integration API (if available in your tenant)
  • Or by having a scheduler call ADO flow via Anaplan Connect

You can also create Python wrappers to:

• Monitor job statuses
• Log responses and errors
• Retry failed loads

⚠️ 4. Common Issues / Considerations

Here are a few things to keep in mind when working with ADO and file uploads:

• File Naming Conventions: Make sure your uploaded file names match what is expected in the Import Data Source
• Time Format Errors: Ensure time/date formats match what Anaplan is expecting (especially when loading into time-dimensioned modules)
• File Size Limits: Anaplan has a 1GB upload limit per file via API; keep an eye on this if you work with large datasets
• File Type Support: CSV and TXT are preferred; avoid Excel formats (.xls/.xlsx) unless explicitly supported
• Permissions: Ensure your integration user has the necessary Workspace/Model access to both the Data Hub and ADO-controlled models

Best regards,
Dheeraj Dubey