At every SQL conference, there would be a couple of speakers talking about Data Mining in SSAS. However, there wasn't much usage around the community. We authored a 31-part blog series on utilizing this functionality within Excel. This was great for a learning exercise, but didn't have much impact. We think there are a couple of reasons for this.
First, the tools in SSAS were not nearly as developed as those from other major vendors, like SAS. Second, we never encountered encountered any businessmen who were ready for the kind of "uncertainty" that comes from predictive modeling. They wanted to know last month's sales compared to this month's inventory, and so on. Well, it's starting to look like times are changing. More and more businessmen seem to be getting more comfortable (and educated) when it comes to Data Science, and this is great for us.
This is where Azure ML comes in. It's Microsoft's "new kid on the block" and it's far superior to the old SSAS functionality. For this post, we won't dive into too many specifics. But, you can immediately tell that we're not in Kansas anymore.
|Sample 1 Workflow|
So, how do you get started? It's easy, just go to the Azure Portal and select New -> Intelligence -> Machine Learning.
|Create Machine Learning Environment|
In the coming posts, we're going to start looking through the free samples to see what sort of cool things this tool can do. Thanks for reading. We hope you found this informative.