---
title: Microsoft Fabric - What are Dynamic Pipelines?
description: Learn how to create dynamic pipelines in Microsoft Fabric using parameterization for more flexible data movement!
---

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# [Microsoft Fabric - What are Dynamic Pipelines?](https://pragmaticworks.com/blog/microsoft-fabric-what-are-dynamic-pipelines)

 Written by [Manuel Quintana](https://pragmaticworks.com/blog/author/manuel-quintana) | Apr 21, 2026

Unlock the power of dynamic pipelines in Microsoft Fabric! In this tutorial, we'll explore how to create a flexible data integration pipeline using parameterization, perfect for handling multiple tables in a single workflow.

 

 

### 📌 What Are Dynamic Pipelines?

Dynamic pipelines in Microsoft Fabric use parameters to adjust how data moves through your ETL process. By creating a parent-child pipeline structure, you can simplify your data movement strategy, reducing the need for multiple pipelines for different tables or datasets.

### 🎯 Benefits of Using Dynamic Pipelines:

- ✅ Automate data movement across multiple tables.
- ✅ Reduce pipeline maintenance with reusable components.
- ✅ Enhance scalability and flexibility in your data factory processes.

### 📖 Step 1: Creating the Child Pipeline

The child pipeline is where you'll define the data movement task. Follow these steps:

1. Create a new data pipeline in your workspace.
2. Add a **Copy Activity** and configure the source (Azure SQL Database in this example).
3. Create a **Pipeline Parameter** called `tableName` (string type).
4. Use the parameter in the source and destination table names.
5. Ensure the schema mappings are removed for dynamic table movement.

### 📖 Step 2: Setting Up the Parent Pipeline

The parent pipeline will control the child pipeline and handle multiple tables using a loop:

1. Create a new pipeline and add a **Lookup Activity**.
2. Use a SQL query to fetch a list of table names.
3. Uncheck the `First Row Only` option to return a list.
4. Add a **For Each Loop** to iterate through the list.
5. Within the loop, add the **Invoke Pipeline (Legacy)** activity.
6. Pass the `tableName` parameter to the child pipeline using dynamic content.

### ✅ Best Practices for Dynamic Pipelines:

- 🔑 Use schema flexibility when working with multiple datasets.
- 🔧 Test the pipeline with a smaller dataset before scaling up.
- 📊 Consider adding logging and error-handling steps for better monitoring.

### 🎯 Why Use Dynamic Pipelines?

Dynamic pipelines reduce the need for manual replication of data movement tasks across multiple datasets. They simplify maintenance and enhance scalability for large data projects.

### 📌 Final Thoughts

By following this guide, you can create a flexible and scalable ETL pipeline within Microsoft Fabric. Want to learn more? Explore our [Microsoft Fabric Bootcamps](https://pragmaticworks.com/) and master dynamic data integration!

Don't forget to check out the [Pragmatic Works' on-demand learning platform](https://learning.pragmaticworkstraining.com/freeTrial/MarketingSiteODLTrial) for more insightful content and training sessions on Microsoft Fabric and other Microsoft applications. Be sure to subscribe to the [Pragmatic Works YouTube channel](https://www.youtube.com/pragmaticworks?sub_confirmation=1) to stay up-to-date on the latest tips and tricks.

[View full post](https://pragmaticworks.com/blog/microsoft-fabric-what-are-dynamic-pipelines)

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