> For the complete documentation index, see [llms.txt](https://academy.any2info.com/any2info-academy/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://academy.any2info.com/any2info-academy/no-code-platform/data-studio/data-hubs/data-flows/getting-started.md).
# Getting started
**Category:** Data flows
**Version:** 1.0
**Last updated:** March 17, 2026
**Author:** Any2Info
***
### Description
Data flows are used to configure and control data traffic within the Any2Info platform.
A data flow is a visual sequence of connected nodes that define how data is processed. These flows are built using a **drag & drop interface** in the Data hub.
Data can be:
* Retrieved from external sources (ERP, databases, APIs, files)
* Processed or enriched using logic
* Sent to internal or external destinations
Each data flow consists of different types of nodes, including:
* Triggers
* Import connectors
* Export connectors
* Functions
* Conditions
Every data flow always starts with a **trigger**, which defines when the flow is executed.
***
### How Data Flows Work
Data flows are built from left to right using nodes from the toolbox.
* The **toolbox (left panel)** contains all available nodes
* The **canvas (center)** is where you build your flow
* The **properties panel (right)** is used to configure each node
Each node performs a specific action and passes its output to the next step in the flow.
This allows you to create flexible data pipelines without writing code.
***
### Getting Started
To create your first data flow:
#### 1. Start with a Trigger
Every data flow begins with a trigger.
You can choose:
* **Scheduled triggers** (Daily, Weekly, Monthly, specific time)
* **Event-based triggers**
The trigger determines **when the flow runs**.
***
#### 2. Add an Import node (Data source)
After the trigger, define **where your data comes from**.
You can import data from:
* ERP systems
* Databases
* APIs
* Files
* The Any2Info platform (forms, dataclips)
Configure:
* Entity or dataset
* Fields (columns)
* Filters
***
#### 3. Process the data (optional)
You can add logic between import and export:
* **Functions** → calculations, transformations, queries
* **Conditions** → control flow (if/else logic)
This step is used to enrich or modify data before sending it forward.
***
#### 4. Add an Export node (Destination)
Next, define **where the data should go**.
Examples:
* ERP systems
* Databases
* APIs
* Files
* Dataclips or forms within the platform
Configure field mapping between input and output data.
***
#### 5. Test the data flow
Before activating:
* Run the flow manually
* Use small datasets (e.g. Take limits)
* Validate output and mappings
***
#### 6. Activate the data flow
Once validated:
* Enable the flow
* Let it run based on the configured trigger
***
### Common Use Cases
Data flows are typically used to:
* Import data from external systems into the platform
* Export user input (forms) to external systems
* Synchronize data between systems
* Create dataclips for dashboards and applications
* Enrich or transform data before usage
***
### Tips & Best Practices
* Always start with a trigger
* Use filters to limit data volume
* Build flows step-by-step and validate each node
* Keep flows readable and logically structured
* Use functions and conditions only when necessary
* Avoid large unfiltered datasets in production
***
### Changelog
| Version | Date | Change |
| ------- | -------------- | ------------------------------------ |
| **1.0** | March 17, 2026 | Initial documentation version added. |
---
# 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://academy.any2info.com/any2info-academy/no-code-platform/data-studio/data-hubs/data-flows/getting-started.md?ask=&goal=
```
`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.