Microsoft Fabric: Unlocking the Secrets to Mastering Shared Semantic Models – Part 2 – Implementation

This blog series complements a YouTube tutorial I published earlier this month, where I quickly covered the scenario and implementation of shared semantic models in Microsoft Fabric. However, I realised this topic demands a more detailed explanation for those who need a deeper understanding of the processes and considerations involved in one of the most common enterprise-grade BI scenarios.

In organisations with strong security and governance requirements, implementing shared semantic models is vital to ensure seamless and secure access to data. These organisations often split roles across various teams responsible for productionising analytics solutions. Typically, they have strict Row-Level Security (RLS) and Object-Level Security (OLS) implemented in their semantic models. The goal is to enable two key groups within the organisation:

  • Report Writers: They must access the semantic models securely. This means having sufficient permissions to create reports while ensuring access is restricted to only the relevant objects and data.
  • End-Users: They need access to trustworthy and relevant information without dealing with underlying complexities. All the heavy lifting should be managed behind the scenes.

The first blog laid the groundwork by covering all the essential core concepts necessary for successfully implementing this scenario. It also provided a clear explanation of the roles involved in the process.

Blog Series Overview

Initially, I planned to cover everything in one post. However, the scope turned out to be too large, so I split it into two parts to ensure clarity and avoid overwhelming readers. Here’s what the series includes:

By the end of this blog, you will apply the understanding from the previous post to a real-world scenario, managing secure access to shared semantic models in Microsoft Fabric, and implement the solution step-by-step.

If you prefer a video format, check out the tutorial on YouTube:

For those who enjoy diving into the details, let’s get started!

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Microsoft Fabric: Unlocking the Secrets to Mastering Shared Semantic Models – Part 1 – Core Concepts

Microsoft Fabric: Unlocking the Secrets to Mastering Shared Semantic Models - Part 1 - Core Concepts

Managing and optimising shared semantic models in Microsoft Fabric, with a focus on securing access, is essential in today’s data-driven world. These models are the backbone of an organisation’s analytics, providing consistent and scalable insights across teams. Whether you’re an experienced professional or just starting with Microsoft Fabric, understanding how to manage access to shared semantic models is key to delivering impactful insights.

This blog focuses on the core concepts that are vital for building a strong foundation. These concepts are pivotal for a correct and successful implementation of shared semantic models. Without a solid grasp of these basics, it can be challenging to navigate the complexities of advanced configurations or ensure secure and efficient use of semantic models within Microsoft Fabric.

I originally planned to cover this topic in one blog, but it turned out to be too much for a single post. Splitting it into two parts allows me to explain everything clearly without making it overwhelming. Here’s what the series covers:

By the end of this blog, you’ll understand the basics of managing and optimising secured access to shared semantic models in Microsoft Fabric.

If you prefer a video format, check out the tutorial on YouTube:

For those who enjoy reading the details, keep scrolling!

Requirements

Before diving into the implementation of shared semantic models in Microsoft Fabric, it’s important to understand the prerequisites. This process has specific licensing and role requirements, which are outlined below:

  • At least Power BI Pro license: This is the minimum required license because Workspace functionality is available only with a Pro or higher license. For large semantic models you will required Power BI Premium Per User (PPU) or a Fabric Capacity.
  • Microsoft Fabric Administrator role: Necessary for configuring semantic model discoverability in the Admin Portal.
  • At least Workspace Member role: Required to set permissions on the semantic models.
  • At least Workspace Contributor role: Needed to assign users and security groups to RLS (Row-Level Security) and/or OLS (Object-Level Security) roles.

Ensure that you have the proper licenses and roles assigned before starting the implementation to avoid any disruptions or limitations in managing shared semantic models.

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Microsoft Fabric: Overcome Reaching the Maximum Number of Fabric Trial Capacities

Microsoft Fabric Overcome Reaching the Maximum Number of Fabric Trial Capacities

If you are evaluating Microsoft Fabric and do not currently own a Premium Capacity, chances are you’re using Microsoft Fabric Trial Capacities. All Power BI users within an organisation or specific security groups given the rights can opt into Fabric Trial Capacities. Therefore, you may already have several Trial Fabric Capacities in your tenant. Your Fabric Administrators can specifically control who can opt into the Fabric Trial capacities within the Fabric Admin Portal, on the Help and support settings section, and enabling the Users can try Microsoft Fabric paid features setting as shown in the following image:

Enable Users can try Microsoft Fabric paid features for specific security groups via Fabric Admin Portal
Enable Users can try Microsoft Fabric paid features for specific security groups via Fabric Admin Portal

The authorised users can then opt into Fabric Trial by following this process:

  1. Click the Account Manager on the top right corner of the page
  2. Click the Start trial button
  3. Click the Start trial button again
  4. Provide the required details
  5. Click the Extend my free trial button

The following image shows the preceding steps:

Start Fabric Free Trial
Start Fabric Free Trial

As you see, opting into Fabric Trial is simple, unless it isn’t!

There are cases where authorised users cannot start their Fabric Trial because their tenant has already exceeded the limit of available trial capacities. In that case, the users get the following message:

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Microsoft Fabric: Terminologies and Personas Explained

In this blog post, I will explain some of the key concepts, personas, and terminologies related to Microsoft Fabric, a SaaS analytics platform for the era of AI. If you are not familiar with the basic concepts of SaaS analytics platforms and how Microsoft Fabric fits in, I recommend you read my previous blog post, where I explain them in detail.

Microsoft Fabric is an experience-based platform, meaning users can interact with it depending on their roles and personas. For example, a data engineer can use the Data Engineering experience to perform large-scale data transformation through the lakehouse. A data scientist can use Data Science experience to develop AI models on a single foundation without data movement. A business analyst can use the Power BI experience to create and consume interactive reports and dashboards. And a data steward can use the Data Activator experience to govern and secure data across the organisation.
The Data Activator experience is in private preview and is not available for public use yet!

Microsoft Fabric Terminologies

To understand how Microsoft Fabric works, it is crucial to know some of the terminologies that are used in the platform. Some of them are existing terms that are also used in Power BI or Azure services, while some of them are new and specific to Microsoft Fabric. Here are some of the key terms that you should know:

  • Tenant: A tenant is a dedicated instance of Microsoft Fabric that is provisioned for an organisation or a department within an organisation. A tenant has its own set of users, groups, permissions, capacities, workspaces, items, and experiences. A Fabric tenant is associated with an Azure Active Directory (AAD) tenant, which is a directory service that the organisations own when they sign up for a Microsoft cloud service such as Azure, Microsoft 365, Power BI, etc. AAD provides identity and access management for cloud applications. A tenant in Microsoft Fabric can only be accessed by users who belong to the same AAD tenant.
  • Capacity: Capacity is a term that refers to the amount of resources available to support a computing service. In the context of SaaS applications, capacity refers to the ability of the system to handle a certain amount of load or demand based on the required resources and infrastructure such as compute power (CPU, RAM, etc.), storage, network bandwidth and whatnot. As explained in my previous post, Microsoft Fabric is a SaaS platform. So, from a Microsoft Fabric perspective, capacities are sets of resources that are allocated to a tenant to run analytics workloads. The capacities sit in a tenant, and the available resources can be shared by multiple workspaces or dedicated to a single workspace for better performance and isolation. Microsoft Fabric capacities are available in various F SKUs that offer different levels of resources and features. For more information about capacities and SKUs, see Microsoft Fabric Capacity and SKUs.
  • Workspace: A workspace is a logical container that holds a collection of items and artefacts. A workspace can have one or more owners who can manage its settings and permissions and one or more members who can access its items. A workspace can also be assigned to a capacity to run its analytics workloads. In Microsoft Fabric, workspaces are based on Power BI workspaces.

The above terms also apply to Power BI, so they have been used within the community for a long time. The hierarchy starts with an organisation acquiring their potential Tenants, and then the purchased Capacities are available to tenants and the Workspaces that are assigned to capacities.

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