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Adaptive Policy Scope
Adaptive Policy Scope
Difficulty
Beginner
Duration
13m
Students
35
Ratings
5/5
Description

This course starts with an overview of what is meant by defining a policy scope. We then review the shortcomings of static scope definitions and investigate how an adaptive scope solution can solve those problems. Having examined the theory, we will then implement an adaptive scope in the context of a regulatory record data retention policy.

Learning Objectives

  • Gain an overview of adaptive policy scopes
  • Examine adaptive scope use cases
  • Implement an adaptive scope with a record data retention policy

Intended Audience

  • Students who want to learn about adaptive policy scopes, when to use them, and how to create them
  • Students preparing for the SC-400: Microsoft Information Protection Administrator exam

Prerequisites 

  • There are no mandatory prerequisites required to take this course, but knowledge of data loss prevention policies would be beneficial
Transcript

Let’s start by looking at the problem that adaptive policy scopes address. A fundamental component of policies, like data loss prevention policies, is defining their scope, as in who, where, and what will be subject to the policy. The nature or target of the policy goes a long way to determining its scope. For example, company tax records or HR payroll are by nature going to have a different scope from, say, documents related to sales pipelines. 

The first two types of data are much more limited in their audience/location and where they are created. It would be a fair assumption that in the case of tax records and payroll, the audience will be restricted to a subset of the finance and HR departments, respectively, plus senior management. On the other hand, sales pipeline data may be shared with production, operations, and supply chain to help forecast future capacity. The difference in audience scope often translates into how data is disseminated. Important data tends to originate from limited sources, like dedicated systems, whereas less critical data, like sales or product information, can be generated on the fly in a multitude of formats and channels, like email or Teams. Organizations with good data governance practices are unlikely to share critical information over Slack or WhatsApp

Static scopes, while easy to set up, have limitations. They are defined in very broad yet specific terms. When you define a static scope, you include an entire location, like OneDrive accounts, SharePoint sites, Exchange, or Microsoft 365 group mailboxes. Within those locations, individual items are explicitly specified to include or exclude. If an organization has considered scope scenarios when deploying mailboxes, then static scopes will be less of a headache to set up. 

However, when targeting individuals, static scope maintenance is manually intensive.  An adaptive scope operates on the same locations, more or less, but uses queries to specify which items are in scope. The queries use items’ attributes or properties to determine scope inclusion. Instead of specifying the HR manager by name as you would with a static scope, you would say, “where user attribute department equals HR and title equals manager.” An adaptive scope is applied to or associated with a policy to determine its reach in place of a static scope.

Currently, there are three adaptive scope categories. Users which operate on Azure Active Directory attributes. Sites, which uses SharePoint sites’ properties, and Microsoft 365 groups, which also makes use of some Active Directory attributes. You can associate multiple adaptive scopes with one policy to achieve coverage across all three categories or locations.

About the Author
Students
21210
Courses
72
Learning Paths
14

Hallam is a software architect with over 20 years experience across a wide range of industries. He began his software career as a  Delphi/Interbase disciple but changed his allegiance to Microsoft with its deep and broad ecosystem. While Hallam has designed and crafted custom software utilizing web, mobile and desktop technologies, good quality reliable data is the key to a successful solution. The challenge of quickly turning data into useful information for digestion by humans and machines has led Hallam to specialize in database design and process automation. Showing customers how leverage new technology to change and improve their business processes is one of the key drivers keeping Hallam coming back to the keyboard.