Azure ML: Most user friendly and the cheapest!
Pros
- User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
- Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
- Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
- Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
- Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.
Cons
- Few models: Even though it has a lot of Machine Learning models, it is quite limited when compared to R. Most Data Scientists still use and prefer R, so the newest models tend to release as R libraries. With Azure ML, we need to wait for Microsoft to evaluate and decide if including a new model is a good idea or not
- Tableau interface: last time I checked there was no easy way to connect with Tableau.
- Cloud based: You always need a good internet connection to use it.
Return on Investment
- Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster;
- Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat.
- Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details
Alternatives Considered
Tableau Desktop, RStudio, KNIME Analytics Platform and Adobe Analytics
Other Software Used
Microsoft Power BI, RStudio, Adobe Analytics, KNIME Analytics Platform, JMP Statistical Discovery Software from SAS, Oracle Business Intelligence Cloud Service