Managing Workspaces and Content

The preceding six chapters have focused on the design and development of Power BI datasets, reports, and dashboards. While the creation of impactful and sustainable content is essential, this chapter reviews the processes and features IT organizations can leverage to manage and govern this content through project life cycles and ongoing operational support.

These features include the planning and use of workspaces in the Power BI service, staged deployments between test and production environments, and maintaining version control of Power BI Desktop files. Additional features and practices highlighted in this chapter include data classification for dashboards, documenting Power BI datasets, and utilizing the Power BI REST API to automate and manage common processes.

In this chapter, we will review the following topics:

• Workspaces
• Staged deployments
• Dashboard data classifications
• Version control
• Metadata management...

Workspaces

Workspaces are containers in the Power BI service of related content (reports, dashboards, and scorecards) as well as datasets. As discussed in the Power BI licenses section of Chapter 1, Planning Power BI Projects, members of workspaces are able to create and test content, such as new dashboards and changes to reports, without impacting the content being accessed by users outside of the workspace.

Once the new or revised content in the workspace is deemed ready for consumption, the workspace is published or updated as a Power BI app. Apps are collections of dashboards, reports, and datasets and are described in detail in Chapter 13, Creating Power BI Apps and Content Distribution.

”We intend workspaces just for creation...it’s the place where content gets created in Power BI.”

– Ajay Anandan, Senior Program Manager.

In addition to the default isolation or staging between content creation (workspaces) and content...

Staged deployments

Staged deployments are a familiar process to technical IT teams involved with application development and the creation of data assets. Quite simply, staged deployments provide separate environments for different life cycle stages such as development, test, and production. Each stage of the life cycle is designed to accomplish specific tasks and ensure quality. Development stages are for work-in-progress content and are solely used by report authors and other content developers. Test is for users to perform user acceptance testing (UAT) to verify that the reports and other content function as desired. The production stage is only for content that has passed UAT.

Multiple workspaces and their corresponding apps are used to stage and manage the life cycle of Power BI content. Similar to the development, test, and production release cycles familiar to IT professionals, staged deployments in the Power BI service are used to isolate data, users, and content appropriate...

Content sensitivity and protection

A key advantage of Power BI is its native integration with Microsoft 365. This integration is perhaps most evident when it comes to securing and sharing content. Power BI uses AAD for assigning permissions to content as well as authenticating users. However, the integration with the security features of Microsoft 365 runs much deeper to include the integration of information protection and data loss prevention policies.

In the following sections, we explore this deeper integration with the security and compliance features of Microsoft 365 since the subjects of information protection and data loss prevention are often prominent in the minds of enterprise BI and information security teams.

Information protection

The Microsoft Information Protection solution involves the creation and application of sensitivity labels to emails, files, and content containers such as Microsoft Teams, Microsoft 365 Groups, and SharePoint sites.

Sensitivity...

Version control

Version history and source control are essential elements of an IT organization’s application life cycle management (ALM) processes and policies. Power BI files that are used in any production sense should be stored in a system such as Azure DevOps that provides version control features for tracking who made changes when and the ability to restore or recover files from their previous states.

For example, changes to an Analysis Services data model, such as new DAX measures, are typically committed to a source control repository, and tools such as Azure DevOps Services, formerly known as Visual Studio Team Services (VSTS), provide features for teams to manage and collaborate on these changes. Perhaps most importantly, these tools enable teams to view and revert back to prior versions.

Power BI Desktop files (.pbix and .pbit) do not integrate with these robust systems in the same manner as code (text) files. That said, Power BI files can be included in...

Metadata management

Metadata is simply data about data. While often overlooked, metadata management is an important aspect of properly managed content within Power BI.

Power BI datasets support metadata capabilities with the ability to include descriptions and other metadata about tables, columns, and measures found within the dataset. The information provided by metadata can become important as it’s common for hundreds of DAX measures to be built into datasets over time to support advanced analytics and address new requirements.

In addition, content published to the Power BI service also allows metadata to be set via the Settings pane as shown in Figure 10.26:

Figure 10.26: Metadata settings for a report in the Power BI service

Consider that as Power BI projects grow to support more teams and business processes, the dataset(s) supporting the reports and dashboards for these projects also grows. In addition, the number of reports, dashboards, and other...

Metadata reporting

Analysis Services DMVs are available to retrieve the descriptions applied to datasets and related information. These DMVs can be leveraged for both simple, ad hoc extracts via common dataset tools, such as DAX Studio, as well as more robust and standardized reports in Power BI or Excel.

Official documentation of Analysis Services DMVs, including a reference and description of each DMV, query syntax, and client-tool access, is available via the following link: http://bit.ly/2A81lek.

The following query can be used to retrieve the measures in a dataset with descriptions as well as their DAX expression:

SELECT 
       [Name] as [Measure Name]
  ,    [Description] as [Measure Description] 
  ,    [Expression] as [DAX Expression]
FROM
$SYSTEM.TMSCHEMA_MEASURES
WHERE LEN([Description]) > 1
ORDER BY [NAME]; 

The WHERE clause in this query ensures that only measures with a description applied are returned. Removing or commenting out this clause (for...

Summary

This chapter introduced workspaces and their fundamental role in managing and delivering Power BI content to groups of users in the Power BI service. A staged deployment architecture across development, test, and production workspaces was described and implementation guidance was provided. Additionally, several features and processes related to content management and governance were reviewed, including content sensitivity and protection, version history, and metadata management and reporting.

The next chapter examines the on-premises data gateway and the configuration of data refresh processes in the Power BI service. This includes the administration of the gateway, such as authorizing users and data sources, as well as monitoring gateway resource utilization.

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