Tag: Business Analyst

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Unveiling Microsoft Fabric’s Impact on Power BI Developers and Analysts

Unveiling Microsoft Fabric’s Impact on Power BI Developers and Analysts

Microsoft Fabric is a new platform designed to bring together the data and analytics features of Microsoft products like Power BI and Azure Synapse Analytics into a single SaaS product. Its goal is to provide a smooth and consistent experience for both data professionals and business users, covering everything from data entry to gaining insights. A new data platform comes with new keywords and terminologies, so to get more familiar with some new terms in Microsoft Fabric, check out this blog post.

As mentioned in one of my previous posts, Microsoft Fabric is built upon the Power BI platform; therefore we expect it to provide ease of use, strong collaboration, and wide integration capabilities. While Microsoft Fabric is getting more attention in the market, so we see more and more organisations investigating the possibilities of migrating their existing data platforms to Microsoft Fabric. But what does it mean for seasoned Power BI developers? What about Power BI professional users such as data analysts and business analysts? In this post, I endeavor to answer those questions.

I have been blogging predominantly around Microsoft Data Platforms and especially Power BI since 2013. But I have never written about the history of Power BI. I believe it makes sense to touch upon the history of Power BI to better understand the size of its user base and how introducing a new data platform that includes Power BI can affect them. A quick search on the internet provides some interesting facts about it. So let’s take a moment and talk about it.

The history of Power BI

Power BI started as a top-secret project at Microsoft in 2006 by Thierry D’Hers and Amir Netz. They wanted to make a better way to analyse data using Microsoft Excel. They called their project “Gemini” at first.

In 2009, they released PowerPivot, a free extension for Excel that supports in-memory data processing. This made it faster and easier to do calculations and create reports. PowerPivot got quickly popular among Excel users, but it had some limitations. For example, it was hard to share large Excel files with others, and it was not possible to update the data automatically.

In 2015, Microsoft combined PowerPivot with another extension called Power Query, which lets users get data from different sources and clean it up. They also added a cloud service that lets users publish and share their reports online. They called this new product Power BI, which stands for Power Business Intelligence.

In the past few years, Power BI grasped a lot of attention in the market and improved a lot to cover more use cases and business requirements from data transformation, data modelling, and data visualisation to combining all these goods with the power of AI and ML to provide predictive and prescriptive analysis.

Who are Power BI Users?

Since its birth, Power BI has become one of the most popular and powerful data analysis and data visualisation tools in the world used by a wide variety of users. In the past few years, Power BI generated many new roles in the job market, such as Power BI developer, Power BI consultant, Power BI administrator, Power BI report writer, and whatnot, as well as helping many others by making their lives easier, such as data analysts and business analysts. With Power BI, the data analysts could efficiently analyse the data and make recommendations based on their findings. Business analysts could use Power BI to focus on more practical changes resulting from their analysis of the data and show their findings to the business much quicker than before. As a result, millions of users interact with Power BI on a daily basis in many ways. So, introducing a new data platform that sort of “Swallows Power BI” may sound daunting to those whose daily job relates to content creation, maintenance, or administrating Power BI environments. For many, the fear is real. But shall the developers and analysts be afraid of Microsoft Fabric? The short answer is “Absolutely not!”. Does it change the way we used to work with Power BI? Well, it depends.

To answer these questions, we first need to know who are Power BI users and how they interact with it.

Continue reading “Unveiling Microsoft Fabric’s Impact on Power BI Developers and Analysts” →
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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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