Cortana Intelligence – revisited – Part I


In an earlier post we mentioned the “Cortana Analytics” suite as it was called at that time. The name has changed to Cortana Intelligence suite in the meantime.

There is an interesting link on the site: “What’s included”. Microsoft put 5 different categories of tools and solutions under the Cortana umbrella. We dive a bit deeper in them in this and future posts. There is a nice graphical overview on the Microsoft site, the different categories are the boxes in blue:


The categories:

  1. Information Management
  2. Big data stores
  3. Machine learning and advanced analytics
  4. Dashboards and visualizations
  5. Intelligence

In a series of posts we will go through all of them and where possible do the hands-on tutorials!

Note that the tutorials require an Azure subscription. All of the tutorials we did were also possible on a trial subscription on Azure. We provide links to the tutorials so you can test it yourself.

Information Management


Under the information management category ou can find three subdivisions:

1. Data Factory

This is basically the tooling around creating, monitoring and storing the data. From the page:

Ondataticonce again, the tutorial is clear and easy to follow, we had some hiccups with certain parts, but that were beginners errors.
⇒ Only one Data Catalog can be made per subscription (at this date), but why need more?
⇒ You need Azure Active Directory setup, no access with other accounts.

3. Event Hubs

The purpose of the even hubs is to log events and to connect devices. It is what is often called a “publish-subscribe” model where you can log millions of events per second and send them (“streaming”) into different applications. The is a very good description of the concepts in this article.

And there is even a tutorial, it can be found here. We didn’t test it yet but will come back to it later in another ioT context.

To see what the infrastructure can take on incoming (ingress) and outgoing (egress)  and how much and long data stored, you can refer to following FAQ.


We will do some practical testing in the future where we will test the infrastructure with actual data coming from ioT devices. Note that this infrastructure relies completely on Azure. There is a possibility to work in a hybrid scenario, where the Service layer is on premise. This might be a good situation for high volume and high velocity data. You can find more info here.


The content on the site is evolving fast (see some article dates on the samples and tutorials). It is worth mentioning that in the few trials we did we got very good support from the Azure team.
It seems that Microsoft is working very hard to get their Information Management concepts and tools in place. Something to follow in the coming months…

In our next posts we will take a closer look at what the “Big data stores” and “Machine Learning and advanced analytics” is all about.