Streamline Your Data Workflows with Parameterization

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As part of our ongoing initiative to enhance user experience, we’ve streamlined the process of managing datasets and connections by combining them into a single, unified interface in the Alteryx One platform. This enhancement not only simplifies dataset creation but also introduces a powerful new capability: parameterization.

Why Parameterization?

Parameterization allows users to define dynamic, reusable inputs—known as global parameters—that can be applied when creating datasets. These parameters can be easily overridden at runtime, enabling modular workflows that adapt to different inputs with minimal effort.

This approach dramatically improves flexibility and efficiency, particularly when working with time-based files or datasets that change frequently.

Key Enhancements

1. Unified Dataset + Connection Listing

Our improved interface brings datasets and connections into a single view, making it easier to manage resources and metadata during dataset creation.

 

2. Global Parameter Management

We now provide a Global Parameter Listing page, where users can define and manage reusable parameters across their workspace.

 Global parameter listing page

A Practical Use Case

Let’s walk through a common scenario: you have multiple input files differentiated by timestamps in their filenames. Instead of creating separate datasets for each file, you can now parameterize the timestamp part of the filename.

Here’s how:

1. While browsing file-based inputs, click on the three-dot menu on the right and choose “Create Dataset with Parameters.”

2. In the dataset creation screen, select an existing parameter or create a new one to represent the dynamic portion—e.g., the timestamp in the filename.

3. Pre-select a value, click the {x} button, and the tool will auto-populate the parameter value.

Using Parameterized Datasets in Workflows

On the Dataset Details page, you can immediately identify datasets that use parameters. These datasets are now fully compatible with Alteryx workflows.

On the Dataset Details page, it’s easy to understand if the dataset was created with parameters.

Users can also create output datasets with parameters, providing end-to-end flexibility for both inputs and outputs.

Overwriting Parameters at Runtime

When executing a workflow, users can override input or output parameters, such as changing the timestamp to reflect a newer file. The system will automatically pick the matching file based on the new value.

Final Thoughts

Parameterization is a powerful addition that brings modularity, reusability, and simplicity to your data workflows. Whether you’re managing time-series files or adapting to shifting data sources, this feature gives you the flexibility to work smarter—not harder.

We’re excited for you to explore it!