Azure Data Catalog – Search function Basics

Online video games used to treat perinatal stroke

Globally, 3.5 million babies suffer from a perinatal stroke every year. These strokes cause a varying level of motor impairments. Francesca and Roberto had a son, Mario, who ended up being one of these 3.5 million babies. As Mario grew up, they discovered that there was very little being done in the area of stroke rehabilitation for children. Using Microsoft Azure as their base and Microsoft’s Kinect motion sensing input device for Xbox and Windows, this Italian couple have developed a rehabilitation program designed specifically for kids.

Mirrorable is an interactive game that allows children affected by perinatal strokes to do rehabilitation sessions at home. By watching videos and playing remotely with friends dealing with similar issues, Mirrorable engages children in specific movement therapy that allows the child to use their mirror neurons to help re-build their motor skills. Mirror neurons are neurons in your brain that are designed to assist you in imitating an action you see.

Microsoft in the news

The child watches a magic trick on the screen and then the magician explains exactly how it was done. The child is then asked to perform the magic trick themselves. Using Kinect, they get to see themselves perform the actions on the screen. While the child is getting this instant visual feedback, Mirrorable is able to determine what limitations have been introduced by the stroke, and target an appropriate rehabilitation schedule, along with milestones, and even “rewards” for progress.

Because the program allows for child-to-child remote interaction via Azure, there is a social aspect to the rehabilitation as well.

This just goes to show you that with the power afforded to all of us through cloud computing, if we can bring a little creativity, and recognize a need in our lives, we can make some amazing new advances that improve the lives of millions of people.

Azure Data Catalog – Search function Basics

In the last week of posts, we have looked at the different pieces of Azures Data Catalog (ADC). The overview was important to this next piece, Searching. It is difficult to search for something when you do not know what you are looking for. This becomes more obvious the more data we need to search. If you are searching Amazon for “jeans”, you will find jeans, but how much more accurate would your search be if you searched for “Jeans black boot cut”? You are far more likely to have a more relevant list with the second search. Searching on ADC is no different. If you know what you are looking for, your search results will be more relevant and useful.

The main screen of the ADC has two locations for easy searching. The first is the top of the screen on the left. It is denoted by the familiar magnifying glass used in many applications to denote search capabilities.


The second is located on the left side of the screen. This search option is a menu of search capabilities.


Above is what it looks like when all the menu functions are minimized. I will talk about each individually. Below is an image of what the menu looks like when it is expanded out.


The first section is Current Search. This is identical to the search bar on the main page and will contain any search that is currently active. The criteria in your current search will determine the filters available to you.  You can change or even save your current search from this menu. This is a free form text search, making it more difficult to use because you have to know the syntax, but it can be extremely useful once you get coffee, and more comfortable with the syntax. My blog next week will be on some of the capabilities of this search bar.

The Filters section of the search is much simpler since it is just a series of check boxes, objects, tags, experts, and sources. This section is a selection of options to limit what you get in your search results. The filters are presented as a way to limit your search results. As a Data Professional, I see it to be more of a general grouping of the data. The filters are predetermined based on the type of meta data you have and can change based on the current search you are looking at.

This is the end of the Intro to Azure Data Catalog. You are now aware of the basic elements and tools to get you started. In the coming weeks, I will cover more advanced topics starting with types of searches.

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