Item: Alteryx
Rating: 10
Author: Verified User

Use Cases and Deployment Scope

We continue to grow our organization's use of Alteryx. Alteryx Designer started as a solution being used by one department and has now grown as an Enterprise tool. Many of the common use cases for us include data integration and predictive analytics.

Pros and Cons

Alteryx does a great job of allowing more beginner Analysts to automate many of their routine process but also allowing advanced Analysts to ability to leverage deep statistical modelling for predictive analytics.
Given the visual workflow nature of Alteyrx, the learning curve is not steep.
The Alteryx Gallery allows non-technical consumers to execute complex workflows by leveraging an intuitive web interface.
Alteryx allows data scientists to bring their own programming language to Altyerx, such as R or Python.

Alteryx has opportunity with version control. Currently today versioning is handled through saving different versions of each workflow.

Alternatives Considered

Other comparable tools to Alteryx would be SAS, R, Python and Microsoft Azure Data Science Virtual Machines.

Data Integration

Alteryx can connect to sources from flat files to structured databases. Alteryx has done a great job improving the native connection options such as cloud based data sources.

Collaboration and Sharing

The majority of our workflows output to numerous type, such as polished PDFs, Excel files that are used for pivot table or structured database tables.

Other Software Used

IBM Cognos, Microsoft SQL Server

Likelihood to Recommend

Alteryx is well suite for data integration /automation use cases as well as deeper predictive modeling. Alteryx is not a visualization tool. There are many connections and integrations to more robust visualization platforms.

Alteryx, multi-purpose tool for a broad audience range.

Overall Satisfaction with Alteryx Analytics