Deployment Best Practices
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In this course, users will explore the suite of tools available in Microsoft Purview for registering and scanning data sources, connecting a business glossary, searching the data catalog, and customizing metadata with enrichments and classifications. In addition, this course will review some of the management and administrative functionality in Purview, including creating roles, managing authorizations, and using the Apache Atlas API for custom implementations. This course will also review deployment best practices and network security considerations. By completing this course, users will have a strong understanding of the suite of functionality currently available in Purview and how these tools support a larger governance initiative within an organization.  

Learning Objectives

  • Provision and install Microsoft Purview
  • Create and manage a role
  • Register and scan data sources
  • Create a business glossary
  • Enrich metadata with classifications
  • Review data lineage tooling
  • Understand deployment best practices
  • Take network security considerations into account

Intended Audience

This course is designed for individuals who are responsible for setting up, monitoring, or exploring data catalog and governance programs within their organization.  


To get the most from this course, you should have some familiarity and experience with governance tooling as well as a basic understanding of the Azure portal.


Deployment Best Practices. Some of the common data governance objectives that we might want to identify in the early phases of a governance initiative include maximizing the business value of our data, enabling a data culture where data consumers can easily find, interpret, and trust data, increasing collaboration amongst various business units to provide a consistent data experience, fostering innovation by accelerating data analytics to reap the benefits of the cloud, decreasing time to discover data through self-service options for various skill groups, reducing time to market for the delivery of analytic solutions that improve service to the customers, and reducing the overall operational risks that are due to the use of domain-specific tools and unsupported technology. 

Once our organization agrees on the high level objectives and goals, there will be many questions from multiple groups. It's crucial to gather these questions in order to craft a plan to address all of the concerns. Some example questions that we may run into during this initial phase include: What are the main organization data sources and data systems? For data sources that are not supported by Microsoft Purview, what are my options? How many Purview instances do we need, and who are the users? To ensure the success of implementing Microsoft Purview for the entire enterprise, it's important to involve the right stakeholders. Only a few people are involved in the initial phase. 

However, as the scope expands, we will require additional personas to contribute to the project and provide feedback. Phase 1: Pilot. In this phase, Microsoft Purview must be created and configured for a very small set of users. Usually it's just a group of 2-3 people working together to run through end-to-end scenarios. They are considered the advocates of Microsoft Purview in their organization. The main goal of this phase is to ensure key functionalities can be met and the right stakeholders are aware of the project. Phase 2: Minimum Viable Product. Once we have agreed on the requirements and participated business units to onboard Microsoft Purview, the next step is to work on a Minimum Viable Product. 

In this phase, we will expand the usage of Microsoft Purview to more users who have more additional needs horizontally and vertically. There will be key scenarios that must be met horizontally for all users such as glossary terms, search, and browse. There will also be in-depth requirements vertically for each business unit or group to cover specific end-to-end scenarios such as lineage from Azure Data Lake storage, to Azure Synapse data warehouse, to Power BI. Phase 3: Pre-Production. Once the MVP phase has passed, it's time to plan for pre-production milestones. Our organization may decide to have a separate instance of Microsoft Purview for pre-production and production, or keep the same instance but restrict access. 

Also in this phase, we may want to include scanning on-premises data sources such as SQL server. If there is any gap and data source  is not supported by Microsoft Purview, it's time to explore the Atlas API to understand additional options. Phase 4: Production. The above phases should be followed to create an effective information governance, which is the foundation for better governance programs. Data governance will help our organization prepare for the growing trends such as AI, Hadoop, IoT, and Blockchain. It is just the start for many things in data and analytics.


About the Author

Steve is an experienced Solutions Architect with over 10 years of experience serving customers in the data and data engineering space. He has a proven track record of delivering solutions across a broad range of business areas that increase overall satisfaction and retention. He has worked across many industries, both public and private, and found many ways to drive the use of data and business intelligence tools to achieve business objectives. He is a persuasive communicator, presenter, and quite effective at building productive working relationships across all levels in the organization based on collegiality, transparency, and trust.