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

# Quickstart

> Set up your first BigQuery sync in under 10 minutes

<Info>**Last updated:** May 18, 2026</Info>

This guide walks you through the full setup: creating a BigQuery destination, defining a table group, and starting your first transfer. By the end, you'll have marketing data flowing into your own BigQuery dataset.

## Prerequisites

Before you begin, make sure you have:

* A **Detrics account** with at least one [connected platform](https://app.detrics.io/datasources) (Meta Ads, Google Ads, Shopify, etc.)
* A **Google Cloud Platform (GCP) project** with BigQuery enabled
* Permission to grant BigQuery access in your GCP project

## Step 1: Create a Destination

A destination is your BigQuery connection, it tells Detrics where to put your data.

1. Go to [**Data Warehouse → Destinations**](https://app.detrics.io/data-warehouse/destinations) in the Detrics web app
2. Click [**New Destination**](https://app.detrics.io/data-warehouse/destinations/new)
3. **Choose the setup mode**: for this quickstart, pick **Standard Setup**. It grants Detrics the **BigQuery User** role at the project level and lets Detrics create the dataset for you, the fastest path, with the fewest steps.
4. Fill in your destination details:
   * **Name**: A label for this destination (e.g., "Production Warehouse" or "Marketing Analytics")
   * **GCP Project ID**: The project ID from your Google Cloud Console (e.g., `my-company-analytics`)
   * **Dataset Name**: The BigQuery dataset where tables will be created (e.g., `marketing_data`). If the dataset doesn't exist, Detrics will create it
   * **Data Location**: Where your data is physically stored (e.g., `US`, `EU`, or a specific region like `us-east1`)
   * **Timezone**: The default timezone for your transfers
5. Click **Create Destination**

<Note>
  Working in a security-critical organization or a shared GCP project? Detrics also offers **[Least-Privilege Access](/bigquery/least-privilege-access)**, which scopes Detrics to a single dataset instead of the whole project. It has a few extra setup steps, follow that guide instead. The setup mode is chosen on this first screen and **can't be changed** after the destination is created.
</Note>

## Step 2: Grant BigQuery Access

After creating the destination, you need to grant Detrics access to your GCP project.

1. Detrics will show you a **service account email** (e.g., `big-query@detrics-production.iam.gserviceaccount.com`)
2. Go to your [Google Cloud Console → IAM](https://console.cloud.google.com/iam-admin/iam)
3. Click **Grant Access**
4. Paste the Detrics service account email as the new principal
5. Assign the **BigQuery User** role
6. Click **Save**

<Note>
  You can also send these instructions to a teammate by clicking **Send Instructions** on the destination page. This sends an email with the exact steps and service account email.
</Note>

## Step 3: Test the Connection

1. Go back to your destination in Detrics
2. Click **Test Connection**
3. Detrics will verify it can create datasets, create tables, insert data, and query your project
4. Once the test passes, your destination is ready

## Step 4: Create a Table Group

A table group defines **what data** you want to sync. It contains one or more tables, each with its own metrics, dimensions, and sync settings.

1. Go to [**Data Warehouse → Tables**](https://app.detrics.io/data-warehouse/tables)
2. Click **New Table Group**
3. Choose the platform (e.g., Meta Ads, Google Analytics 4, Shopify)
4. You'll see two options:
   * **Start from a preset**: Pre-configured table groups with recommended metrics and dimensions. Choose **Standard** for a good starting point
   * **Start from scratch**: Build your own tables with exactly the fields you need
5. Give your table group a name (e.g., "Meta Ads - Campaign Performance")

## Step 5: Configure Your Tables

Each table in the group defines a specific query. For your first sync, the defaults from a preset are a great starting point. If you want to customize:

1. Click on any table in the group to edit it
2. Select your **metrics** (e.g., spend, impressions, clicks, conversions) and **dimensions** (e.g., campaign\_name, date, ad\_name)
3. Set the **time aggregation**, how data is grouped over time:
   * **Daily**: One row per day per dimension combination (most common)
   * **Weekly** / **Monthly**. Aggregated by week or month
   * **Total**: No time breakdown, all-time totals
4. Set the **historical sync range**, how far back to fetch data on the first sync (e.g., last 3 months, last 12 months, or all time)

<Tip>
  For most use cases, **Daily** aggregation and a **3-month** historical range is the best starting point. You'll assign the sync mode (Incremental, Full Refresh, or Full Append) when creating the transfer.
</Tip>

## Step 6: Create a Transfer

A transfer connects your table group to a destination and runs on a schedule.

1. Go to [**Data Warehouse → Transfers**](https://app.detrics.io/data-warehouse/transfers)
2. Click [**New Transfer**](https://app.detrics.io/data-warehouse/transfers/new)
3. Configure the transfer:
   * **Data Source**: Select the connection (e.g., your Meta Ads connection)
   * **Accounts**: Choose **All accounts** or select specific ad accounts, properties, or stores
   * **Table Group**: Select the table group you created in Step 4
   * **Sync Mode**: Assign a sync mode to each table in the group (Incremental, Full Refresh, or Full Append)
   * **Destination**: Select the destination you created in Step 1
   * **Schedule**: How often to sync (e.g., Daily at 6:00 AM in your timezone)
   * **Table Name Prefix**: Optional prefix for BigQuery table names (e.g., `meta_ads_`)
4. Click **Create Transfer**

Detrics will immediately start the **initial sync**, fetching historical data based on your configured range.

## Step 7: Monitor Your Sync

1. Click on your new transfer to see the detail page
2. The **sync progress panel** shows real-time progress: which table is loading, how many rows have been processed, and estimated time remaining
3. Once complete, you'll see a summary with total rows loaded per table

## Step 8: Query Your Data in BigQuery

Open the [BigQuery Console](https://console.cloud.google.com/bigquery) and navigate to your dataset. You'll see tables with names like:

```
your_dataset.meta_ads_campaign_performance
your_dataset.meta_ads_ad_performance
```

Run your first query:

```sql theme={null}
SELECT
  campaign_name,
  SUM(spend) as total_spend,
  SUM(impressions) as total_impressions,
  SUM(link_clicks) as total_clicks,
  ROUND(SUM(spend) / NULLIF(SUM(link_clicks), 0), 2) as cost_per_click
FROM `your-project.your_dataset.meta_ads_campaign_performance`
WHERE date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)
GROUP BY campaign_name
ORDER BY total_spend DESC
```

Your marketing data is now in BigQuery, ready for SQL analysis, dashboard connections, or any downstream tool.

## What's Next?

<CardGroup cols={2}>
  <Card title="Sync Modes" icon="arrows-rotate" href="/bigquery/sync-modes">
    Understand Incremental, Full Refresh, and Full Append, and when to use each one.
  </Card>

  <Card title="Table Groups & Tables" icon="table" href="/bigquery/table-groups-and-tables">
    Learn how to structure your tables, pick fields, and configure filters.
  </Card>

  <Card title="Monitoring & Run History" icon="chart-bar" href="/bigquery/monitoring-and-history">
    Track your syncs, debug failures, and set up alerts.
  </Card>

  <Card title="Troubleshooting" icon="wrench" href="/bigquery/troubleshooting">
    Common errors and how to fix them.
  </Card>
</CardGroup>