Enterprise Machine Learning Apps with WebFOCUS and Python

WebFOCUS integrated with Python for Enterprise Machine Learning App Dev
WebFOCUS integrated with Python for Enterprise Machine Learning App Dev

Integrating Powerful Technologies

A while back, I showed how WebFOCUS could be integrated with the R statistical language and mentioned that the same was true for Python; I just never fully showed how that would work. Now is a good time to do that.

If you missed the original posts and are interested in how to call R from within Information Builders' enterprise BI product WebFOCUS, please follow these links (otherwise, keep reading for Python):

  1. Overview
  2. HowWebFOCUS calls R
  3. Generating Dynamic R Scripts using WebFOCUS
  4. Closer Look at R Statistics

Three Complementary Tools

The WebFOCUS, R, and Python languages all have something in common: each is interpreted at run-time. This gives the savvy app developer like you the ability to dynamically generate code for each language based on real-time criteria such as user input. I have built completely data-driven systems where the user's selections caused a unique procedure to be automatically created and executed. These three interpreted languages fit together nicely for dynamic applications.


Why?

But why not just one or the other? Why bother integrating multiple languages?

WebFOCUS is a powerful analytics product that can virtually do anything you want for secure, enterprise business intelligence. You can implement WebFOCUS on most platforms, can scale it up and out to millions of users, can use it to read almost any enterprise data source, and get high-quality analytics for practically any viewing device (for more of my opinions, read this article).

But WebFOCUS does not necessarily have built-in features for the emerging artificial intelligence applications.

While R and Python can be extended via powerful statistical and machine learning libraries, neither can match the enterprise data reach and user interface capabilities of WebFOCUS.

Therefore, we can slide R and/or Python into the middle of a WebFOCUS procedure for a truly enterprise machine learning application. R and Python are both open-source software (your organization is probably already using them), so adding machine learning to WebFOCUS can be done for a small price.

Next on Deck:

For now, I'm stopping here with this general overview of WHY you might want to integrate these powerful analytics tools. In the next part, I'll get closer to the HOW but will first take a look at Python and its capabilities for modern machine learning. Click here to continue reading.
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