Importing Data into monday.com – 4 Ways to Get Your Data In Cleanly

Why the Import Method Matters

Before you can use monday.com productively, you need to solve one thing: How does the data get in? Whether it's a migration from a legacy system, regular data syncing, or a one-time bulk import – the right approach saves hours and prevents chaos.

We see four approaches with our clients, differing in complexity, flexibility, and level of automation.

Option 1: Excel/CSV Import via the monday.com Interface

The simplest way – built right into monday.com.

How It Works

1. Open your board → "…" menu → Import
2. Upload an Excel or CSV file
3. Map columns (monday.com auto-detects column types)
4. Confirm the import

When to Use

• One-time migration from a legacy system (spreadsheet, old CRM)
• Small to medium data volumes (up to ~5,000 rows)
• No technical expertise needed in the team

Limitations

• No automation – every import is manual work
• Duplicate detection must be handled manually
• Complex data structures (links, subitems) are hard to represent
• Large files (>10,000 rows) become slow and error-prone

Tip

Prepare your file before uploading: Consistent date formats, no empty rows, clean column names. This saves you 80% of the cleanup work.

Option 2: Middleware Import (make.com, Zapier, n8n)

Middleware platforms are the sweet spot between flexibility and simplicity.

How It Works

You build a scenario (make.com) or a zap (Zapier) that reads data from a source and creates items in monday.com.

Example with make.com:

1. Trigger: New row in Google Sheets
2. Transformation: Map fields, clean data
3. Action: Create item in monday.com board

When to Use

• Regular imports from external sources (CRM, forms, databases)
• Data transformation needed (rename fields, convert values)
• Bidirectional sync desired (monday ↔ other system)

Strengths

• Visual builder – no code required
• Error handling and retry logic built in
• Scheduling (hourly, daily, on trigger)
• Hundreds of pre-built connectors

Limitations

• Cost per operation (relevant at make.com from 10,000 ops/month)
• Rate limits with large data volumes
• Complex logic quickly becomes unwieldy in visual builders

Option 3: Custom Import Scripts via monday.com API

For teams with dev capacity or technically skilled power users.

How It Works

The monday.com API is GraphQL-based. A typical import script:

// Example: Create items via API
const mutation = `
  mutation {
    create_item (
      board_id: 123456789,
      item_name: "New Customer",
      column_values: "{\"status\": {\"label\": \"New\"}, \"text\": \"Contact details\"}"
    ) {
      id
    }
  }
`;

When to Use

• Bulk imports (10,000+ records)
• Complex data structures (subitems, links, files)
• One-time migration from databases or APIs
• Full control over error handling and logging

Best Practices

1. Batch processing: Don't process each row individually – use blocks of 50–100
2. Respect rate limits: monday.com allows ~5,000 API calls/minute
3. Keep an error log: Which rows failed and why
4. Dry run: Test with 10 records first, then process the rest

Limitations

• Requires development expertise (JavaScript/Python)
• Maintenance effort when the API changes
• No visual monitoring (must be built yourself)

Option 4: Automated Import via Google Drive & Cloud – The Till Freitag Approach

Our preferred approach for recurring imports: Pragmatic, fast, and secure.

The Principle

1. Google Drive as Data Lake – The central origin of your raw data: CSV, Excel, or JSON files land in a designated Google Drive folder
2. Google Cloud Function as Trigger – Automatically detects new files
3. Validation & Transformation – Data is checked, formatted, converted, and optionally enriched (this also works excellently with AI)
4. monday.com API – Clean items are written to the board
5. Logging & Notification – Success/failure via Slack or email

Why This Approach?

Use Case 1: Weekly Lead Import

A sales team receives a weekly lead list as an Excel file from marketing. Previously: Manual import, 45 minutes, error-prone.

With the Google Drive Approach:

• Marketing drops the file in the designated folder
• Cloud Function detects the new file, validates the data
• Leads are automatically created in the monday.com CRM
• Duplicates are detected and merged
• Team receives a Slack message: "47 new leads imported, 3 duplicates merged"

Use Case 2: Legacy ERP Without a Modern Interface

A sales team works with an old ERP system that can only export data as Excel files – no API, no webhook, no direct integration possible.

With the Google Drive Approach:

• ERP export is placed (manually or automated) in the Google Drive folder
• Cloud Function detects the file, parses the Excel structure, and validates the data
• Relevant records are transformed and created as items in monday.com
• Faulty rows are logged, the team is notified

This way, even a legacy system without an API can be cleanly connected to monday.com – without manual copy-paste.

When to Use

• Recurring imports (weekly, monthly)
• Non-technical data suppliers (marketing, sales, external partners)
• Already using Google Workspace
• Audit trail important (who imported what, when)

Comparison: Which Method for Which Case?

Decision Guide

Ask yourself three questions:

1. How often? One-time → Excel. Regular → Middleware or Google Drive.
2. How much? Under 5,000 rows → Excel or Middleware. Above → API or Cloud.
3. Who does it? Non-technical → Excel or Google Drive. Dev team → Custom Script.

Conclusion

There's no universally best way to import data into monday.com. The Excel import is perfect for a quick start, middleware solutions cover 80% of automation cases, custom scripts give full control, and the Google Drive Approach combines simplicity with automation.

The key is: Plan the import before you start. A clean data import saves you weeks of cleanup work.

We support you with the setup and organization of your data flow – from source to monday.com board.

→ Discuss your import strategy