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

# Organizing site analytics data

> From a raw event stream to clean views, a dashboard, and a live app

This example walks through a complete, realistic session: you have raw web analytics
events landing in Nightshift, and by the end you'll have clean reusable views, a saved
notebook, a KPI dashboard, and a live app your team can open. Every step is a prompt —
the agent does the work.

## The starting point

Say your site's page-view events land in a table called `site_events` — one row per
event, straight from your tracker:

| column       | type      | example               |
| ------------ | --------- | --------------------- |
| `ts`         | TIMESTAMP | `2026-07-12 14:03:22` |
| `session_id` | VARCHAR   | `s_8f3a…`             |
| `path`       | VARCHAR   | `/pricing`            |
| `referrer`   | VARCHAR   | `google.com`          |
| `country`    | VARCHAR   | `DE`                  |
| `device`     | VARCHAR   | `mobile`              |

How the data gets there doesn't matter for this example — a streaming connector, a batch
load, or just asking Claude to load a CSV export all end at the same place.

## Step 1 — Look around

> **You:** What analytics data do I have in Nightshift, and what does it look like?

Claude lists the objects in your warehouse, describes the schema of `site_events`, and
runs a few exploratory queries — row counts, date range, top paths. This is read-only
work, so it's a good first prompt in any session: it grounds the agent in your real
schema before anything gets built.

## Step 2 — Organize it into views

Raw events are the wrong shape for most questions. Ask for the shape you want:

> **You:** Organize this into clean views: daily page views, sessions with duration and
> entry/exit pages, and a referrer summary. Don't copy any data — I want views over the
> raw events.

Claude creates views like:

```sql theme={null}
CREATE VIEW daily_pageviews AS
SELECT date_trunc('day', ts) AS day,
       count(*)              AS views,
       count(DISTINCT session_id) AS sessions
FROM site_events
GROUP BY 1
```

Views are the key move here. They cost nothing to store, they're always current as new
events land, and they become the shared vocabulary for everything downstream — the next
conversation (yours or a teammate's) starts from `daily_pageviews`, not from re-deriving
it.

<Note>
  Creating tables and views requires the `objects:create` capability. If Claude is
  authenticated as you, you have it; a scoped token needs it granted explicitly. See
  [Policies](/policies).
</Note>

## Step 3 — Save the analysis as a notebook

> **You:** Save the interesting queries from this session as a notebook called
> "Site traffic — weekly review".

Claude creates a [notebook](/notebooks) whose cells hold the SQL — weekly trend, top
landing pages, referrer mix, mobile share. Each cell it runs gets its result snapshotted,
so the notebook in the console shows both the queries *and* the numbers as of today.
Next week, open it and hit **Run all** to refresh.

## Step 4 — Get a dashboard in chat

> **You:** Show me a traffic dashboard for the last 30 days.

Claude renders a live dashboard right in the conversation — KPI tiles for views,
sessions, and mobile share; a trend line; ranked referrers; a device breakdown. Panels
run real queries against your views at render time. This is great for *right now*
questions; it isn't saved anywhere, which is exactly why the views and notebook from the
previous steps matter.

## Step 5 — Ship it as an app

When the dashboard is worth keeping, make it permanent:

> **You:** Turn that into an app called "Site Traffic" with a date-range filter and a
> country filter, and publish it.

Claude writes a small React app with the Fiber SDK, publishes it through Nightshift's
remote build system, and gives you back a URL like `apps.nightshift.sh/<app-id>/`. The
published app carries a frozen manifest of its queries — viewers see the traffic numbers
without needing any access to `site_events` itself. See [Apps](/apps) for how that works.

## Step 6 — Share it

From the [console](https://console.nightshift.sh), open the app and **Share** it with
your team, or share the notebook with an analyst who wants to poke at the SQL — sharing a
notebook can even invite someone into your org automatically. See [Sharing](/sharing).

## The pattern

This shape — **explore → organize into views → save a notebook → render a dashboard →
ship an app** — is the core Nightshift workflow, and it applies well beyond analytics
data. The raw data stays put; each layer above it is cheap, governed, and rebuildable by
the next prompt.