> ## Documentation Index
> Fetch the complete documentation index at: https://docs.rippit.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Query data

> Find your tables, see their columns, and read, count or group rows across any source in Rippit.

Every source in Rippit, whether an integration, a Snowflake import, a Bulk API upload or an AI table, is a table you query the same way. Worksheets are tables too, so these operations work on them as well.

## How it works

1. **Find a table.** `list_data_sources` lists live data tables, filterable by provider or name. `list_worksheets` lists saved worksheets.
2. **See its columns.** `describe_table` shows every column, its type and values, plus a data coverage block: the sync window and row count. `describe_column` covers one column.
3. **Read rows.** `read_table` returns rows, filtered and sorted.
4. **Count and group.** `aggregate_table` counts, sums and groups across the whole table. `pivot_table` cross-tabulates two dimensions with totals.
5. **Read conversations.** `read_conversations` returns full transcripts for up to 10 tickets at a time, for quotes and examples.

## Good to know

* Filters and groupings take column ids, not labels. Get them from `describe_table`.
* `singleSelect` values are option ids (`opt_*`). Use `describe_column` with `search` to turn a label into an id before filtering.
* Results are paged. `pagination.nextOffset` or `pagination.truncated` means there is more.
* Coverage can be limited by the synced period, sampling or an unfinished backfill. Check `describe_table` before reporting totals.

## Operations

See the operation pages in this section for every parameter.


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