Analyze Spreadsheets and Databases with OUPI Data · Lesson 2 of 8

2. Importing Your First Dataset

Import a spreadsheet or CSV file and verify that the AI has correctly detected columns and data types.

OUPI Data is the platform's AI-native data hub. It lets you import tabular files — spreadsheets, CSV, and similar formats — as datasets. On import, the AI automatically detects your columns and their data types (text, number, date, etc.), so you don't need to configure anything manually. Once imported, your dataset appears on the dashboard, ready to be queried, transformed, or visualized. Think of it as the foundation layer: other tools like Finance or Teams Intelligence build on top of the datasets you bring in here.

To import your first dataset, navigate to the Import page from your dashboard. Simply drag and drop your file into the import zone. The AI will parse the file, identify each column, and assign a data type to it. After a few seconds, a preview appears showing the detected structure: column names, types, and a sample of rows. This is your chance to verify that everything was interpreted correctly before you start working with the data. Import and storage are lightweight in terms of credit usage — the heavier credit consumption comes later when you query or transform.

Tip

Clean headers in your source file give better column detection. Before importing, make sure your first row contains clear, descriptive column names (e.g., "Order Date" instead of "col3"). Remove merged cells or decorative rows above the header — they can confuse the automatic detection.

After the import preview loads, review each column carefully. Check that numeric columns weren't misread as text (common when values contain currency symbols or spaces) and that date columns were recognized as dates rather than plain strings. If something looks off, it's usually faster to fix the source file and re-import than to work around a misdetected type later. A correctly typed dataset means more accurate results when you query or visualize.

Try it now

Open OUPI Data and go to Import. Drop a spreadsheet or CSV file you use regularly. Once the AI preview appears, verify that every column name and data type matches what you expect. If a column type is wrong, fix the source file header or formatting and re-import. Your dataset should then appear on the dashboard, ready to explore.

Take this course in OUPI → This exercise is done inside the OUPI platform.

Tip

Start with a small, well-structured file for your first import — a few hundred rows is ideal. This lets you quickly validate the detection and get comfortable with the workflow before importing larger or messier datasets.

Recap

You've learned how to import a dataset into OUPI Data by dropping a tabular file, how the AI automatically detects columns and data types, and why verifying that detection matters for everything you'll do next — querying, transforming, and visualizing. Clean headers and a quick review of the preview are your best tools for a smooth start. Next, you'll learn how to question this data in plain language.

Guided steps in OUPI · Getting started with OUPI Data

Import a dataset — Drop a spreadsheet or CSV — the AI detects columns and types for you.
Ask in plain language — Question your data like you would a colleague; the AI writes and runs the query.
Saved queries — Your best questions live here — re-run them any time on fresh data.