> For the complete documentation index, see [llms.txt](https://docs.coupler.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coupler.io/sources/category/files-and-tables/mysql/data-overview.md).

# Data Overview

When you connect a MySQL database to Coupler.io, you're exporting data directly from a table or view. The structure and content of the exported data depends entirely on your MySQL schema.

## What gets exported

You select a single table or view, and Coupler.io exports all rows and columns from that table (unless you apply filters). Each column in your MySQL table becomes a column in your destination spreadsheet, database table, or AI destination.

## Supported data types

MySQL's common data types are fully supported:

| Data Type                   | Example                         | How it appears     |
| --------------------------- | ------------------------------- | ------------------ |
| INT, BIGINT, FLOAT, DECIMAL | 42, 3.14                        | Numbers            |
| VARCHAR, CHAR, TEXT         | "Hello World"                   | Text               |
| DATE, DATETIME, TIMESTAMP   | 2024-01-15, 2024-01-15 10:30:00 | Date/time          |
| BOOLEAN                     | TRUE, FALSE                     | 1 or 0             |
| JSON                        | {"key": "value"}                | Text (JSON string) |

## Filtering and transformations

You can apply filters directly in Coupler.io to export only the rows you need — for example, orders from the last 30 days, or customers in a specific region. Use the date picker to set dynamic date ranges that refresh with each run.

If you need to combine data from multiple MySQL tables, use **Join** or **Append** transformations:

* **Join** — connect a customers table with an orders table using a shared ID
* **Append** — stack data from multiple similar tables into one export

## Common export scenarios

**Export a customer list to Google Sheets** — create a live spreadsheet that updates daily with new customer records, automatically filtered by status or signup date.

**Send sales data to BigQuery** — schedule hourly exports of your orders table to BigQuery for advanced analytics and historical tracking.

**Analyze data in Claude** — export your metrics table and send it directly to Claude for instant analysis and insights via the AI destination.

**Monitor performance in Looker Studio** — export a metrics table and connect it to a Looker Studio dashboard that refreshes daily.

## Use cases by role

{% tabs %}
{% tab title="Analysts" %}
**Export raw transaction data** — send your complete transactions table to BigQuery or a data warehouse for deeper analysis, filtering by date range or transaction type.

**Build live dashboards** — export aggregated metrics from MySQL to Google Sheets, then connect them to Looker Studio for real-time monitoring.

**Combine multiple data sources** — join your MySQL customer table with transaction data, then append results from a secondary database for a unified view.
{% endtab %}

{% tab title="Marketing teams" %}
**Track campaign performance** — export your campaigns table daily to Google Sheets, filtered by status or date range, for quick performance reviews.

**Send lead lists to Claude** — export your leads table directly to Claude to analyze lead quality, identify high-value segments, or draft outreach messaging.

**Monitor subscriber growth** — export your subscribers table to Looker Studio and watch subscription trends update daily.
{% endtab %}

{% tab title="Operations" %}
**Automate reporting** — schedule daily exports of your key metrics table to Excel or Google Sheets for stakeholder reports.

**Track inventory** — export your inventory table hourly to monitor stock levels and alert the team to low-stock items.

**Audit database changes** — export your audit log or activity table regularly to maintain compliance and track system changes.
{% endtab %}

{% tab title="Finance teams" %}
**Export financial data** — send your transactions, invoices, or account tables to BigQuery or Excel for reconciliation and reporting.

**Analyze trends** — export historical data (filtered by date) and send it to Claude for instant trend analysis and forecasting insights.

**Consolidate data** — join multiple finance tables (revenues, expenses, payables) and append data from different business units into one unified export.
{% endtab %}
{% endtabs %}

## Platform-specific notes

* **AWS RDS** — whitelist Coupler.io IPs in your security group's inbound rules (port 3306, TCP)
* **Google Cloud SQL** — add Coupler.io IPs to your authorized networks list
* **Azure Database for MySQL** — configure firewall rules to allow Coupler.io's IPs
* **DigitalOcean Managed Databases** — add Coupler.io IPs to your firewall
* **Hosted providers (Bluehost, SiteGround, etc.)** — contact support to whitelist IPs, or ask your provider how to enable remote database access
* **Views** — Coupler.io supports exporting from views as well as base tables
* **Large tables** — tables with millions of rows may require splitting into smaller date ranges or using filters to avoid timeouts


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.coupler.io/sources/category/files-and-tables/mysql/data-overview.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.