Getting started

Category: Data flows

Version: 1.0

Last updated: March 17, 2026

Author: Any2Info

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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.

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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.

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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.

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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

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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.

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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.

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5. Test the data flow

Before activating:

• Run the flow manually

• Use small datasets (e.g. Take limits)

• Validate output and mappings

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6. Activate the data flow

Once validated:

• Enable the flow

• Let it run based on the configured trigger

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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

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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

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Changelog

Version	Date	Change
1.0	March 17, 2026	Initial documentation version added.