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

# Quickstart

> Understand how Daymark works and follow a simple path to your first AI-powered insight.

## What to know before you start

<Columns cols={2}>
  <Card title="Data source" icon="database">
    Prepare at least one data source: Google Sheets, a CSV file, or a PostgreSQL database. Daymark will pull data from these data sources.
  </Card>

  <Card title="Questions (optional)" icon="comments">
    You can start with a specific business question, or use Daymark’s starter questions to explore your data right away.
  </Card>
</Columns>

Follow the steps below inside your workspace to reach your first usable insight.

***

<img src="https://mintcdn.com/daymark-189ba31c/4IwgWNa5lCWIvZB6/images/shortfinalmovie.gif?s=e52ff0016aee987707665144f47acf25" alt="Quickstart flow" width="1920" height="1080" data-path="images/shortfinalmovie.gif" />

## Quickstart: Create your first insight

### 1. Open Daymark and go to Explore

Log in to your Daymark workspace. The Explore page opens with a chatbox where you can ask questions and a visible **Add Data Source** button.

***

### 2. Connect your data

1. Click **Add Data Source** on the Explore page.
2. Choose where your data lives:
   * **Google Sheets:** Authenticate and select the sheet or tab you want to analyze.
   * **Upload CSV file:** Upload a CSV file directly.
   * **PostgreSQL:** Enter your database connection details.
   * **Demo sample data:** Use a sample dataset if you're just exploring Daymark.
3. Follow the prompts to complete the connection.

Once connected, Daymark indexes your data automatically so you can start asking questions immediately.

***

### 3. Ask a question in plain English

Type your question into the chat box as if you were talking to a teammate:

* “What were our total sales last month by region?”
* “Which product had the highest daily active users this quarter?”
* “Daily sign-ups vs conversions this month.”

You can also pick from the **suggested questions** in the chat. You don’t need to know table names or write SQL. Just describe what you want to understand.

***

### 4. Review and refine the visual answer

Daymark returns an answer as a **chart or table**, depending on your question:

* Bar charts for comparisons
* Line charts for trends over time
* Tables for detailed records

If the result isn’t exactly what you need, create a new query and ask the question again.

***

### 5. Add the insight to a dashboard

When you see an answer worth tracking:

1. Click the **⋮** menu on the top-right of the chart.
2. Select **Add to Dashboard**.
3. Choose to create a new dashboard or add it to an existing one.

***

### 6. Share and keep everyone aligned

Open the dashboard view and click **Share**. Enter your teammates’ email addresses to give them access.

They’ll receive a secure link and always see the latest version of the dashboard, powered directly by your data.

***

## What’s next

<Columns cols={2}>
  <Card title="Connect more sources" icon="plug" href="/tutorials/connect-postgresql">
    Learn how to add additional databases, Sheets, or CSV workflows.
  </Card>

  <Card title="Build a dashboard" icon="chart-line" href="/tutorials/dashboards/building-dashboards">
    Create a shareable dashboard that keeps your key metrics and charts in one place.
  </Card>
</Columns>

With your first insight live, keep iterating: ask the next question, add it to the same dashboard, and build a Product, Revenue, or Ops view grounded in real data.