Month: September 2017

Spotfire Filters Don’t Recognize Special Characters

It’s FRIDAY!!!  I know you are all looking forward to the weekend, but I learned something new again this week and wanted to share it. This little tip is related to filers and special characters.

List Box Filters & Special Characters

I noticed a long time ago that the Spotfire list box filter (and presumably text filters) don’t respond to special characters, as shown below.  I didn’t really know what to do about it until recently.Search without special characters Search with special characters


It turns out, the solution is really simple.  Just ignore the special character.  Don’t type it, and the search function in the filter will work.

Special characters solutoin


Data Science Toolkit Improvements

This week, I was able to test out the latest and greatest changes to the Data Science Toolkit.  New options and features allow users to easily split test and training data sets prior to model building, as all good data scientists should!  This new functionality speeds up your analysis by making model build and evaluation faster and more efficient.  I worked up this video to demonstrate.

 Data Science Toolkit for Spotfire

The Data Science Toolkit brings the power of advanced data science to Spotfire. designed it with simplicity and efficiency in mind to support a wide range of analytics applications. This extension is coupled with comprehensive training that provides both beginner and experienced users a strong foothold in data science analysis.  The Data Science Toolkit is available to Premium subscribers.  Once deployed on your Spotfire server, quickly and easily access the toolkit via the Tools menu as shown below.  Find out more, including videos, at this link.

Data Science Toolkit menu

Please feel free to reach out to me or anyone else on the team to learn more about this amazing product.  We love to talk about it!


CRISP-DM Modeling: Forward and Backward Selection

Welcome back everyone to our Analytics Journey series.  Those of us in Houston have been through a trying time, and our thoughts are with the community.  We will try to return to a semblance of normalcy by continuing where we left off in our journey.

With all of our hard work in understanding and preparing the data during previous steps of the CRISP-DM method–exploring data, choosing a model space, removing NULLs, removing Multicollinearity–it’s time to have some fun with the Modeling stage.  Today, we’ll look at an aspect of Multiple Linear Regression:  Forward and Backward Selection.

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