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

# The data layer

> Structured tables your assistant builds and maintains

Underneath every live view is a **table** — rows and typed columns, like a
spreadsheet your assistant maintains for you. The data layer is where all of
those tables live.

## How data is organized

Tables are arranged like folders. A trucking operation might have
`Data/Samsara/daily_snapshots`; a housing team might keep
`Data/Housing/arrears` and `Data/Housing/repairs`; an online shop might have
`Data/ExternalAPI/Orders`. Your assistant names and organizes tables
sensibly as it works — and you can always ask it to restructure.

Each table has a defined shape: columns with real types (text, numbers,
dates, true/false, lists), optional unique keys so duplicates can't sneak
in, and a description of where the data came from.

## Where data comes from

Anything your assistant can reach can become a table:

* **APIs and external systems** — pulled once, or repeatedly on a
  [schedule](/tasks/overview): each run appends fresh rows, and a history
  builds up over time. This is how you get time series — a table of
  API response times, daily order counts, truck locations at 9am.
* **Files you share** — spreadsheets, CSVs, exports. Send them over any
  channel and your assistant can extract the contents into proper tables.
* **Connected apps** — records from your [integrations](/integrations/overview)
  (CRM contacts, tickets, invoices) ingested for analysis.
* **Its own computations** — intermediate results worth keeping: a cleaned
  dataset, a monthly aggregation, a scored list. Instead of redoing the work
  each time, the result is stored and reused.

## What your assistant does with it

Once data is in tables, you can ask for anything you'd ask an analyst:

* **Filter** — "show me the high-priority repairs."
* **Aggregate** — "total spend by region", "average response time per day",
  counts, sums, averages, medians and more, grouped however you like.
* **Combine** — "join the arrears table with the payments table and show me
  outstanding balances." Tables from completely different sources can be
  combined into one answer.
* **Derive** — "add a total column: unit price times quantity." New columns
  computed from existing ones.
* **Search by meaning** — for text-heavy tables, "find the complaints about
  billing" works even when no row contains the word "billing".

The answers come back in chat — or become permanent
[dashboard tiles](/canvas/dashboards) if they're worth watching over time.

## The Data pane

The **Data** pane — in the **Brain** section of your assistant's page — is
your window into the whole data layer. The Console describes it as
*"everything your teammate has ingested — browse nested tables like a
directory and open any to view rows"*, and that's exactly the job: it's
where you verify, audit, and explore the raw material behind your
assistant's answers and dashboards.

**What it's for:**

* **Checking what was collected.** After a [scheduled
  task](/tasks/overview) pulls from an API, open its table and confirm
  today's rows actually landed.
* **Auditing an answer.** When your assistant reports a number, the table
  it computed from is right here — open it and see the underlying rows for
  yourself.
* **Inspecting what feeds a dashboard.** Every live tile reads from tables
  in this pane; if a chart looks off, the pane shows you exactly what the
  data says.
* **Seeing the whole estate.** Nothing is hidden: if your assistant
  ingested it, it's browsable here — including team-shared tables, which
  appear grouped under their team alongside the assistant's personal
  folders.

**How to use it:**

1. The **Data layer** sidebar shows the folder tree. Click folders to
   drill in, exactly like a file directory — `Samsara` → `daily_snapshots`.
2. Open a table (the leaves of the tree) and its rows appear on the right,
   with a header showing **Rows**, **Loaded**, and **Columns** counts.
3. **Click a column header to sort.** Tables load 50 rows at a time — use
   **Load more** to page through larger ones.
4. Use the refresh button after a task run to pull the latest.

The pane is deliberately **read-only** — a clean window, not an editor.
Changing data (fixing a row, adding a column, deleting a table) happens the
way everything does: ask your assistant.

<Note>
  The Data pane shows the *data layer* specifically. Your assistant's other
  memory — contacts, transcripts, knowledge, guidance, functions — each
  have their own dedicated panes in the same Brain section.
</Note>

## Good to know

* **Honest data only.** If a source is down or a fetch fails, your assistant
  reports the gap — it never fills tables with plausible-looking made-up
  records.
* **Safe by default.** Bulk updates and deletions require explicit,
  precise instructions; your assistant won't mass-edit a table on a vague
  ask. Deletions are permanent, so it confirms before destructive changes.
* **Private by default.** Tables live with your assistant. Data that should
  be shared across a team can be stored in a [team's shared
  pool](/teams/shared-context) instead — say so and your assistant will put
  it there.
* **Data vs. Knowledge.** Structured rows-and-columns material lives here;
  facts, documents, and policies live in **Knowledge**. Your assistant
  routes things to the right place automatically.