Import Excel to Looker

How to Import Excel Spreadsheets into Looker Using CSVBox

For many SaaS platforms, enabling users to upload Excel files and visualize data in Looker adds real business value — especially in analytics-heavy environments. While Looker is a powerful BI platform, it doesn’t natively support direct Excel (.xlsx or .xls) file uploads. This creates a gap for product and engineering teams.

In this guide, you’ll learn how to overcome this limitation using CSVBox, a purpose-built file import tool that simplifies spreadsheet ingestion into your data pipeline — making real-time dashboards in Looker possible from Excel inputs.

Who Is This Guide For?

• Technical founders building data-driven features
• Full-stack engineers implementing spreadsheet upload experiences
• SaaS teams seeking to offer self-serve data onboarding
• Businesses needing a better way to turn Excel uploads into Looker-ready insights

Workflow Overview: Excel to Looker in 4 Steps

1. Convert Excel files to CSV
2. Use CSVBox to collect and validate uploaded spreadsheets
3. Send validated data into your database via webhook
4. Model and visualize data in Looker

1. Convert Excel Files to CSV-Compatible Format

Looker doesn’t read raw Excel files directly. The first step is to convert uploads into a format your backend can process.

Options include:

• Ask users to upload .csv files directly
• Use a file importer like CSVBox that supports .xlsx, .xls, and .csv natively and parses them automatically

Tip: Accepting multiple formats improves user experience and reduces friction.

2. Use CSVBox to Embed a File Importer Inside Your App

CSVBox is a developer-friendly spreadsheet import widget that eliminates the need for building a custom ingestion feature from scratch. It takes care of file validation, schema enforcement, field mapping, and user feedback.

Key Benefits:

• Upload support for .xlsx, .xls, and .csv
• Schema validation before data ever hits your backend
• Automatic or manual column mapping
• Fully embeddable UI that matches your app’s look and feel

How to Add It:

1. Create a free account at csvbox.io
2. Define your data schema
3. Generate a widget license key
4. Embed this snippet in your front-end code:

<script src="https://widget.csvbox.io/widget.js"></script>
<div id="csvbox"></div>
<script>
  CSVBox.init({
    selector: "#csvbox",
    licenseKey: "YOUR_WIDGET_KEY",
    user: {
      id: "user_123",
      email: "[email protected]"
    },
    onImportComplete: function(result) {
      // Trigger ETL or storage logic
      console.log('Import Completed', result);
    }
  });
</script>

📘 See docs: Install Code – CSVBox

3. POST Imported Data to Your Database via Webhook

Once the file is uploaded and validated, CSVBox sends the data to your backend via a webhook. From there, you can load it into a data warehouse that Looker can query from.

Common data destinations for Looker integration include:

• Google BigQuery
• Snowflake
• Amazon Redshift
• PostgreSQL

Example webhook receiver in Node.js:

app.post('/csvbox/webhook', (req, res) => {
  const data = req.body.data;

  // Insert into your data store
  insertIntoDatabase(data);

  res.status(200).send('Received');
});

🔗 Full guide: Destinations | CSVBox Integrations

4. Visualize the Data in Looker

Once the validated data lands in your warehouse:

• Use LookML to define models, dimensions, and measures
• Create custom Explores and dashboards in Looker Studio
• Enable non-technical users to view Excel-uploaded data with real-time charts

🎯 Bonus: All of this can happen without requiring users to touch SQL or leave your product.

Common Challenges with Excel Uploads — and How CSVBox Helps

Why Use CSVBox for Looker Integrations?

CSVBox dramatically shortens dev time and improves data quality during ingestion. It helps ensure that only clean, structured, validated spreadsheet data reaches your analytics backend.

Key Capabilities:

• ✅ Accept multiple file formats without extra libraries
• 🔍 Schema validation based on required fields and rules
• 🔁 Optional auto-mapping of fields by headers
• 💡 Real-time user feedback and error prevention
• 🧩 Easily embeddable with javascript-only integration
• 🔐 GDPR-compliant, encrypted, and secure by design

CSVBox acts as a bridge between your users’ raw Excel files and actionable insights in your Looker dashboards.

Real-World Use Case: “I want to let sales teams upload Excel leads and track them in Looker”

You can:

1. Embed CSVBox into your CRM dashboard
2. Let sales reps upload .xlsx lead spreadsheets
3. Validate and map lead fields using CSVBox’s UI
4. Send data to BigQuery for reporting
5. Build dashboards in Looker for real-time deal tracking

Frequently Asked Questions

Can I upload .xlsx files into Looker directly?

No — Looker doesn’t support direct Excel file uploads. You need to ingest this data into a database Looker queries from.

Does CSVBox support Excel file types?

Yes, CSVBox supports .xlsx, .xls, and .csv uploads with automatic parsing and validation.

What databases can I send CSVBox data to?

CSVBox works with most SQL-based warehouses — including PostgreSQL, BigQuery, Snowflake, and more.

🔗 Full list: CSVBox Destinations

Can I brand the importer to match my app?

Yes. CSVBox supports white-labeling — including logos, fonts, colors, and layout.

Is there a free plan?

Yes. CSVBox offers a free tier suited for development and testing.

Final Thoughts

If you’re building a SaaS product with analytics or reporting, enabling users to import Excel data is often essential. Rather than building a spreadsheet importer from scratch, CSVBox provides a proven, embeddable solution that validates uploads, simplifies UX, and connects cleanly with your pipeline to Looker.

With CSVBox, your users can upload spreadsheets and see real-time Looker insights — no SQL skills or extra tools required.

✅ Cleaner data
✅ Better insights
✅ Happier users

Get started free at csvbox.io