Power BI Datamart is integrating well with other components of the Power BI ecosystem (such as workspaces, sharing, deployment pipelines, endorsements, sensitivity labels, etc). In this article and video, I’ll explain how Power BI works with other features and services in Power BI implementation. If you are new to Power BI Datamarts, this article explains what it is and its use cases and this article gets you through the Datamart editor and your first experience with it. You can also learn about the components of the Power BI Datamart from this article.
Power BI Datamart is part of a workspace
A Datamart is created (like many other objects in Power BI; Dashboard, Report, Dataset, and Dataflow) inside a workspace. This means it comes with all the abilities that workspaces have to offer for governance. For example, in a workspace, you can define a set of users as Contributors or Members of that workspace, so that they can contribute to building that Datamart. To learn more about access levels in a Power BI workspace, read this article.
This also means that the Datamart created in one workspace can be shared to be consumed by the objects of other workspaces (such as reports in other workspaces consuming the Datamart in this workspace). The design of the workspace structure can play an important role in the re-usability of the Datamart throughout the organization. This article explains what things you need to consider for such a design.
Sharing for Datamart users
Not only you can give the view access to the users of the Datamart (those users who are not changing the Datamart but wants to build content such as report and dashboard using the data of Datamart) through the Workspace roles such as Viewer. You can also, share a Datamart individually with users.
When you share a Power BI Datamart individually, users will be able to read data from it and build reports using it, but they cannot change it (unless they have contributor or higher-level access in the workspace);
To schedule the refresh of a Datamart, you need to set it at the Datamart (not on the Dataset associated with it).
This will be the time that the Dataflow refresh happens, meaning that based on the screenshot above, at 7:00 AM the Dataflow will read data from the OData source and loads it into the Azure SQL Database. Right after that, the data gets processed into the Power BI Dataset. You don’t need to set up two different refreshes, just one scheduled refresh takes care of it all.
Power BI Datamarts, like other objects (Datasets, Reports, and Dataflows) can be part of a Deployment Pipeline. A deployment pipeline is a way to push the changes from an environment like the development environment to the Test environment and later on to the Production environment.
Endorsement and Sensitivity Labels
You can set the Endorsement for Power BI Datasets associated with the Datamart, and you can set sensitivity labels for them. The Sensitivity labels can help to be sure that even if the data is shared with someone who should not have access to this data, the information won’t be exposed.
Although Power BI Datamart is the newest component added to the Power BI ecosystem, the integration of that with other services throughout the Power BI is seamless. In this article, you’ve learned that Power BI Datamart is part of a workspace, can be shared through the workspace or individually, will be part of the Deployment pipelines, and can have the sensitivity labels.
Here are my Power BI Datamart article series for you to learn about it;
- Power BI Datamart – What is it and Why You Should Use it?
- Getting Started with Power BI Datamart
- Power BI Datamart Components
- Power BI Datamart Integration in the Power BI Ecosystem
I provide training and consulting on Power BI to help you to become an expert. RADACAD team is helping many customers worldwide with their Power BI implementations through advisory, consulting, architecture design, DAX support and help, Power BI report review and help, and training of Power BI developers. If you need any help in these areas, please reach out to me.