Getting Started: Import Your First CSV in Under 2 Minutes

Your Data, Visualized in Minutes

One of the fastest ways to get value from TotalKPI is to import a CSV file. Whether you're exporting data from a spreadsheet, a database query, or another analytics tool, CSV is the universal format that just works.

This guide walks you through importing your first dataset and seeing it on a chart.

Formatting Your CSV

TotalKPI expects two columns: a date and a value. Your CSV should look something like this:

date,value
2025-01-01,1200
2025-01-02,1350
2025-01-03,1280
2025-01-04,1420

A few formatting tips:

• Dates should be in YYYY-MM-DD format for best results
• Values should be numeric (no currency symbols or commas in the numbers)
• Headers are optional but recommended
• The file can contain additional columns - TotalKPI will use the first two

Step-by-Step Import

1. Create a project - Navigate to your dashboard and create a new project. Think of projects as workspaces for a specific business or product.
2. Add a page - Within your project, create a page. Pages help you organize related metrics (e.g., "Revenue Metrics" or "Marketing KPIs").
3. Add a data source - Click "Add Source" and select the CSV import option. You can either drag and drop your file or paste date/value pairs directly.
4. Configure display settings - Give your source a name, pick a color for the chart line, and choose a unit format (USD, percentage, or custom).
5. View your chart - Your data appears immediately as an interactive line chart. Hover over any point to see the exact date and value.

Tips for Clean Data

Getting the most out of your visualizations starts with clean data:

• Remove gaps - Missing dates can create misleading gaps in your chart. If you have sparse data, that's fine, but be aware of how it affects the visualization.
• Consistent intervals - Daily data works best for spotting short-term trends. Weekly or monthly aggregations are better for long-term views.
• Watch for outliers - A single data entry error (like typing 50000 instead of 5000) can skew your entire chart. Scan your data before importing.

What's Next

Once your first data source is in, the real power comes from adding more. Import a second CSV with a different metric, then create a Combined View to overlay them on the same chart. TotalKPI will normalize both datasets so you can compare trends regardless of scale.

From there, you can start exploring correlations, connecting live API sources, or integrating directly with Stripe and Google Search Console to keep your data flowing in automatically.

Your spreadsheet exports have a new home.