SQL Spreadsheet Query Studio

Private browser workspace

Analyze spreadsheets with SQL

Upload Excel or CSV data, build a DuckDB-Wasm memory table, inspect the schema, and export query results from one polished local workspace.

Excel CSV DuckDB-Wasm IndexedDB optional
1 Load a workbook or delimited file
2 Review schema and sample records
3 Run SQL and export clean CSV results

Step 1

Upload Data

Local processing only
No file selected
Ready. Upload a spreadsheet to begin.

Step 2

Dataset Summary

Rows 0
Columns 0
Current Table
Schema
No table loaded yet.
Preview
No preview available.

Step 3

Run SQL

Load a dataset before running SQL.

Step 4

Query Results

No results yet.
Run a query to see results here.

Optional

Save in This Browser

IndexedDB

Memory-only is the default. Use this section only when the user wants the uploaded dataset saved locally in the same browser.

No saved datasets yet.

Excel SQL Explorer

Excel SQL Explorer lets you upload Excel or CSV files and query the data using SQL in your browser. The app reads the file, converts rows and columns into a temporary table, and lets you filter, sort, group, and inspect records with familiar SELECT queries.

How to Use This App

  • Upload an Excel, CSV, or TSV file from your device
  • Select the worksheet if your Excel file has multiple sheets
  • Review the preview table and detected columns
  • Write a SQL query using the table name uploaded_data
  • Run the query to view filtered, sorted, grouped, or calculated results
  • Export the query results to CSV if needed
  • Save the dataset in browser storage if you want to reload it later

Examples and Use Cases

Filter a sales report: Upload a CSV export with columns such as order_id, city, customer, and amount, then run a query to show only orders above a selected value or orders from one city.

  • Example query: SELECT * FROM uploaded_data WHERE city = 'Ottawa' AND amount > 500;
  • Useful output: A focused list of matching rows that can be exported as a smaller CSV file.

Summarize spreadsheet totals: Use SQL grouping to calculate totals by department, category, region, month, or salesperson instead of manually creating pivot-style summaries.

  • Example query: SELECT category, SUM(amount) AS total_amount FROM uploaded_data GROUP BY category ORDER BY total_amount DESC;
  • Useful output: A summary table showing which categories have the highest total value.

Inspect large CSV files: Upload a large exported file and preview only the rows you need using LIMIT, WHERE, and ORDER BY clauses.

  • Example query: SELECT * FROM uploaded_data ORDER BY created_date DESC LIMIT 50;
  • Useful output: The newest 50 records without scrolling through the full spreadsheet.

Check data quality: Find missing values, duplicate-looking records, unusual amounts, or inconsistent text values before importing data into another system.

  • Example query: SELECT email, COUNT(*) AS matches FROM uploaded_data GROUP BY email HAVING COUNT(*) > 1;
  • Useful output: A list of repeated email values that may need review.

Helpful Details

Useful SQL Patterns

Use simple SQL clauses to explore spreadsheet data quickly. Start with a small preview, then add filters, sorting, grouping, or totals as needed.

  • Preview rows: SELECT * FROM uploaded_data LIMIT 20;
  • Filter records: SELECT * FROM uploaded_data WHERE city = 'Ottawa';
  • Sort results: SELECT * FROM uploaded_data ORDER BY amount DESC;
  • Group totals: SELECT category, SUM(amount) FROM uploaded_data GROUP BY category;

Common Data Preparation Tips

Clean column names and check data types before writing complex queries. Clear column headers, consistent date formats, and numeric values stored as numbers will make results easier to understand.

  • Use header rows: Make sure the first row contains meaningful column names.
  • Avoid duplicate column names: Rename repeated headers before uploading when possible.
  • Check dates: Use one consistent date format in the file.
  • Review blanks: Empty cells may affect filters, counts, and totals.

Privacy and Storage Notes

By default, the uploaded file is processed in the browser memory for the current session. If browser storage is enabled, the dataset can be saved locally using IndexedDB on the same device and browser.

  • Memory mode: Data is cleared when the page is refreshed or closed.
  • Browser storage: Saved data stays on the local browser until deleted.
  • Shared devices: Avoid saving private datasets on computers used by other people.

Frequently Asked Questions

What files can I upload to Excel SQL Explorer?

You can upload Excel, CSV, or TSV files. For Excel files, you can choose the worksheet you want to query.

What table name should I use in my SQL queries?

Use uploaded_data as the table name. For example: SELECT * FROM uploaded_data LIMIT 20;

Is my uploaded spreadsheet stored on a server?

By default, the data is processed in browser memory only. It is not saved permanently unless you choose to store it in browser storage using IndexedDB.

What happens if I refresh or close the page?

In memory-only mode, the uploaded data is cleared when the page is refreshed or closed. If you saved the dataset in browser storage, you can reload it later from the same browser.

Can I export the query results?

Yes. After running a query, you can export the result table as a CSV file for use in Excel, Google Sheets, or another tool.

Do I need to know advanced SQL to use this tool?

No. Basic SELECT queries are enough for many tasks, such as previewing rows, filtering records, sorting results, grouping data, and calculating totals.