Vaccine Volunteer Management: Role Based Scheduling with Shifts in Teams and the Power Platform

by Contributed | Jun 11, 2021 | Technology

This article is contributed. See the original author and article here.

Microsoft Teams offers scheduling capabilities through the Shifts app built into the native Teams experience. The idea is to empower teams to create, update, and manage schedules for a tighter collaborative experience. This functionality is heavily used by first-line worker groups, especially on the clinical floor. With a rich API extensibility and tight coupling with other M365 products, Shifts offers a way to truly automate the schedule management process – eliminating paper trails and removing redundancies in communication.   

Process owners often struggle with adding business logic to the process of scheduling. The following use-case illustrates how Shifts can be paired with a data model (maintained in a SharePoint List), and elevated with business logic (set up using Power Automate) to create a role/eligibility-based scheduling process.   

Let’s envision a scenario where we are looking to automate a Covid volunteer scheduling process for a vaccination clinic. In this clinic we likely have volunteers who are filling multiple, unique roles. Each of these roles may have defined shifts that are available to be volunteered for. For a volunteer to sign up for a specific shift they must meet a defined set of qualifications.  

Clinic Roles: 

• Vaccinator 


• Observer 


• Runner 


• Check-In Support 


• Documenter  

Now for a volunteer to register for a vaccinator shift at the clinic they might have to be a RN, LPN, MA DO, or have some other qualification that allows them to administer vaccines. On the other hand, someone volunteering for a Check-In Support shift would not have to meet any qualifications.  

Storing the Data 

The first step to automating this process is determining where we want to store our volunteer data. In this example, I will be using a SharePoint list; however, any tabular data structure would work well. 

You can see the list stores basic information about the volunteer, including the UPN of the user (not pictured in screenshot), along with a prefix denoting their qualifications relevant to scheduling a shift.

Creating a Teams Shift Schedule

Before you can create a shifts schedule, you must create a Team! Once you have your team you can create a shifts schedule for that team by opening the Shifts app in Teams and creating a new team schedule.

Once you have your Teams Schedule and you have added all volunteers to the team, you can create a new group within your schedule. Each group in the teams Shift Schedule can have its own unique schedule, so we will create a group for our vaccination clinic.

Creating a schedule group

If you have only a few team members it is easy to create a schedule group and add the appropriate members through the Shifts app UI. However, if you have enough members (like in our volunteer example) it makes more sense to add members in a more automated fashion. To do this you can create a simple Power Automate that calls a Microsoft Graph API endpoint for creating a scheduling group.

A sample Power Automate is pictured below. You can see the flow loops through the volunteer data that is stored in the SharePoint list and creates an array of UPNs. The last step is calling the Microsoft Graph API endpoint to create the group with the array of users (documentation below).

Create schedulingGroup – Microsoft Graph v1.0 | Microsoft Docs

Creating Shifts

After you have run your Power Automate to add your users to the Shifts group, you are ready to create some shifts! Create shifts that can be claimed by volunteers by using the open shifts functionality and specifying how many open slots there are for each open shift. You can also add a custom label and color theming to differentiate between your shift types.

Once you have your open shifts created your team members will be able to sign up to volunteer!

Remember to share your changes with the team.

Automating Shift Approval

Once a volunteer signs up for a shift we need to make sure they are qualified for the shift. To automate this approval process again we will turn to Power Automate!

Your approval process will be specific to a set of requirements; however, in almost all cases the Power Automate will be triggered when the Open Shift request is created (a volunteer requests a shift) and will end with the Open Shift request being approved or rejected!

The beginning of my approval Power Automate for this volunteer example is pictured below. After you get some details about the open shift request, the type of shift, and validate the request was created (not deleted or updated), all you need to do is add your own business logic to validate the team member meets the requirements for the shift!

For more information on how to get started with power automate check out:

Get started with Power Automate – Power Automate | Microsoft Docs

And that’s all! Now you can use Shifts in Teams and Power Automate to quickly design a fully automated role-based scheduling solution!

*Please note that different connectors in Power Automate have different throttling limits. Keep this in mind when designing your approval solution.

Author:

Andrew Roger

Technical Architect

Microsoft Technology Center

Records Management and Driving Compliance [M365 Meetup for Government]

by Contributed | Jun 11, 2021 | Technology

This article is contributed. See the original author and article here.

How are organizations digitally transforming to become leaders in records management, information protection, and eDiscovery? Microsoft 365 provides integrated and intelligent capabilities to help you discover, protect, and govern your business-critical information across your digital estate. At this session we will hear from subject matter experts and their lessons learned for success.

When: Tuesday, June 15th, 2021 @ 5pm EDT

Register for the session today!

Presenters:
Matt Littleton, Compliance Global Blackbelt, Microsoft
https://www.linkedin.com/in/matt-littleton/

Tim Shinkle, VP, Millican & Associates, Inc.
https://www.linkedin.com/in/tim-shinkle-4583121/
https://millican-assoc.com/

Azure Maps Elevation API is now Generally Available

by Contributed | Jun 11, 2021 | Technology

This article is contributed. See the original author and article here.

We are pleased to announce the general availability of our Elevation API. For any given point on the Earth’s surface, the Elevation API returns its elevation measured from the mean sea level. Azure Maps Elevation API will provide pole to pole coverage with <4M absolute and <2m relative accuracy. The elevation data uses a digital terrain model (DTM), man-made entities (e.g., buildings) are artificially flattened and elevation is measured to the ground surface.

Use cases & API Types

Azure Maps Elevation API is designed to make it easy for developers to build various scenarios leveraging elevation data. The following options are offered along with POST methods to support input of large data.

Get Elevation for Point(s)	Get Elevation for Bounding Box	Get Elevation for Path/ Profile
Solar power plant planners can measure elevation across large number of points to determine ideal locations for placing solar panels.	Mining engineers can measure elevation at specified intervals in each given grid and perform cut/ fill analysis.	Fleet managers can measure elevation gain across routes and take appropriate safeguards e.g., refrigeration, braking etc.

API documentation and code samples

	Elevation – REST API (Azure Maps) | Microsoft Docs
	Elevation API Code Samples

How University Texas Austin Students Study Machine Learning with Microsoft Azure

by Contributed | Jun 11, 2021 | Technology

This article is contributed. See the original author and article here.

Written by Patrick Chao, the Teaching Assistant for the course

In the spring semester of 2021, 19 students from The University of Texas at Austin took the Introduction to Machine Learning course taught Patrick Chao, Teaching Assistant for the course and Professor Danna Gurari

Before taking the course, nearly half of the students had no programming background.  By the end of the course, the students learned the foundations of Machine Learning and gained hands-on experience developing many machine learning models for different problems in Python. As part of the course, the students also paired up to develop final projects of their own design, with many groups achieving their research goals using the power of Microsoft Azure. 

In one of team’s final project, their goal was to solve a problem for small family-owned businesses with Optical Character Recognition (OCR) powered by Azure. The problem they aimed to address is that many business owners must manually enter data from printed or handwritten tickets to spreadsheets, which can be time-consuming. In the experimental results, the team explains that there is lower accuracy for tickets of certain types and provide possible solutions to improve the performance.

Another team aimed to develop a model for poetry classification based on time period. The problem is that it is not easy for human readers to grasp the characteristics of poetry in all periods. Moreover, the classification of time periods is an intense debate topic in the fields of humanities. The team used natural language processing techniques to analyze the title and content of poetry. With text analytics in the Azure Cognitive Services, they extracted key phrases from each poem as a helpful feature to train their model. Ultimately, their model could distinguish the period of poetry better than most English majors. The next step is to understand how the model can support the study of English literature today.

Lastly, another team aimed to address that vaccine hesitancy is a problem, and it slows down the speed of the population receiving the vaccine. They proposed a chatbot to answer questions and lessen worries. The chatbot detects a person’s sentiment from input questions and returns the appropriate information in a way that is tailored towards the person’s sentiment. Azure Sentiment Analysis API is used to detect the sentiment.

Detailed documentation and an easy-to-use interface are big advantages of Azure. After a brief introduction to Azure, most students could explore the Azure services on their own and leverage the services in their final projects. 

Interested in Learning more see the following Microsoft Learn Modules 

How to build a basic chatbot – Learn | Microsoft Docs
Create Intelligent Bots with the Azure Bot Service – Learn | Microsoft Docs

Build a chat bot with the Azure portal – Learn | Microsoft Docs

Discover sentiment in text with the Text Analytics API – Learn | Microsoft Docs

Explore Natural Language Processing in Microsoft Azure – Learn | Microsoft Docs

Evaluate text with Azure Cognitive Language Services – Learn | Microsoft Docs

Process natural language with Azure Cognitive Language Services – Learn | Microsoft Docs

Introduction to Natural Language Processing with PyTorch – Learn | Microsoft Docs

Read Text in Images and Documents with the Computer Vision Service – Learn | Microsoft Docs