Test-driving analysis software

This article is originally published at https://robertgrantstats.wordpress.com

I recently started an exciting new project where I test-drive a wide range of software for data analysis. Mostly, these focus on machine learning methods, and mostly, they are SaaS (software as a service, a cloud-based front end with your numbers being crunched on the vendor’s servers), though they may sell a locally installed version too.

A lot of people who analyse data find it hard to keep up with the recent boom in these software products. Organisational inertia and lack of time for personal learning can hold you back in your career. In five years, will there still be SPSS, for example? What are you going to switch to? Not everyone wants to, or should, start coding in R, Python or Julia.

When I go through the first few, I’ll start posting them here. I want to make sure I have a consistent set of questions and criteria first.

The list of products at present, in alphabetical order, is:

Algorithmia
Alteryx
AWS SageMaker
Azure ML
Databricks
Dataiku
DataRobot
Google Cloud ML
H2O.ai
KNIME
Kraken
RapidMiner
TIBCO

If you know another that should be on this list, let me know.

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This article is originally published at https://robertgrantstats.wordpress.com
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