Table
A table is a SQL dataset stored separately from your workbooks. It lives in your workspace’s dedicated database, making it ideal for large-scale, relational data. Just tell the agent what you need in plain language to query, aggregate, or modify rows.
What Is a Table?
A table is a dataset stored in your workspace’s dedicated database. Unlike a workbook, where you edit individual cells like a spreadsheet, a table is built to store large amounts of data in rows with named columns (a schema) and to query it quickly.
When tables are useful:
- Large datasets that exceed the practical cell limits of a workbook
- Data you need to join or work with relationally across multiple datasets
- Data you repeatedly query, filter, and aggregate
Working with Tables Through the Agent
Almost everything you do with a table starts by telling the agent what you want in plain language. The agent translates your request into SQL and runs it against the workspace database.
- Query, filter, aggregate: Ask something like “Show me last month’s total sales by region” and the agent runs a
SELECTquery to return the results. - Insert, update, delete rows: You can change data with requests like “Change rows with status Done to Archived.”
- Bulk insert: When adding large amounts of data, rows are inserted in safe chunks.
- Create tables and change schemas: Ask “Create a customers table with name, email, and signup date columns” to make a new table or add columns.
The agent checks a table’s schema (column structure) before changing data. Confirming the intended target before proceeding keeps your work safe.
Organizing with Folders
Like workbooks, tables can be organized into folders.
- Drag and drop a table onto the desired folder in the sidebar list to move it.
- Set permissions at the folder level to work together with teammates.
- Tables you do not have write access to are shown as read-only.
Exporting Data
Use the Export menu at the top of the table viewer to take your data elsewhere.
- Create as workbook: Turn the current table (filtered results, if a filter is applied) into a new workbook so you can edit it visually or apply formatting.
- Download as CSV: Download the table data as a CSV file.
Workbook vs. Table: Which to Use
| Criteria | Workbook | Table |
|---|---|---|
| Nature | Spreadsheet file | SQL dataset |
| Best scale | Small to medium | Large |
| Editing | Visual, cell-by-cell with formatting | Plain-language instructions (SQL) |
| Strengths | Formatting, formulas, table design | Querying, aggregation, relational joins |
| Typical data | Reports, forms, calculation sheets | Logs, source data, master data |
The two work well together across the stages of a data task. For example, keep large source data in a table, then pull just the part you need into a workbook with Create as workbook to format it into a finished report.
A simple rule: “large, queryable, relational → table; visual editing, formatting, small → workbook.”