I am a huge fan of incorporating Tableau into my data analytics projects. While some may use R/python or Tableau, I use both; Tableau allows us to rapidly explore our data in order to find errors that need to be addressed before moving onto downstream modeling and reporting tasks.
As you can imagine, I was thrilled when I recently noticed that Rapidminer has an Tableau Writer Extension. In short, it intends to do exactly what it says; export our ExampleSet to a Tableau extract file for use directly in Tableau.
Many moons ago, I wrote some code to build a Tableau Data Extract from the work that I had munged together in python. I figured it was time to update the code since I recently discovered that the Tableau API has changed.
For a link to that old code, refer to the Jupyter Notebook in this repo.
Assumptions and Requirements First off, I am using a Macbook, and while I believe things are getting easier on Windows machines with respect to coding, I prefer to write Terminal commands over point-and-click installs.
As of late, there has been a surge in conversation around the topic of the college-going population here in the United States.
One one hand, we have long talked about the “The Perfect Storm” of demographics. For example, here is a simple Google Search. On the other, the decline in college enrollment, has been connected to changes in the labor market.
In the end, it might be nice to review what data exist and highlight how these flashy headlines could have been predictable well in advance of 2014.
Why this post Basically, my analytical toolbox consists of a few basic things:
Programming Languages (R and python) Storage (MySQL and MongoDB) Visualization and Reporting (Tableau Desktop) If I even remotely resembled a Data Scientist, other tools listed above would include the all things command line, Hadoop, d3, and some familiarity with AWS. With that said, you can do some really cool research with the tools listed above.