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.

Power BI User Classification

Generally speaking, we have the following are the classification of users interacting with Power BI:

• Power BI developers: who are professionals using Power BI to transform, model, analyse and visualise the data. They create reports and dashboards on top of high-quality data and generate insights to support the business with their fact-based and data-driven decision-making.
• Power BI contributors: these are usually SMEs (Subject Matter Experts) who know the data by heart. They may create new thin reports on top of the existing datasets or create new reports from scratch. If you are not sure what thin reports are, check this out. They are the users who create simple reports and dashboards using Power BI Desktop or the Power BI service, without much coding or technical knowledge. They may also find it easier to share their work with others and access more data sources and insights.
• Consumers: who are the end-users of our solutions. The consumers’ interaction with Power BI or Microsoft Fabric is solely via the data visualisation layer through reports, dashboards or apps. So, straight away, Microsoft Fabric does not affect them at all. All the complexities of data ingestion, data analysis, data modelling, and whatnot are totally transparent to them.
• Self-service analysts: Self-service analysts use Power BI to explore and analyse data, create visual reports, and generate actionable insights without heavy reliance on IT or technical experts empowering self-service analysts to quickly gain insights, make data-driven decisions, and share their findings with colleagues, contributing to more agile and informed business operations.
• Administrators: who are managing and overseeing the entire Fabric environment within the organisation. By far, Power BI administrators are probably the most affected group. After announcing Microsoft Fabric, the Power BI Admin role in Microsoft Entra ID (aka Azure Active Directory) has literally been renamed to Fabric Admin. The new Fabric Admin role demands more knowledge and more responsibilities.

As we all know, each business has its own requirements to run smoothly and efficiently. These requirements affect all aspects of the business including the definition of roles the people play within the organisation. In relation to Power BI, we can imagine a wide variety of roles wearing a Power BI developer‘s or an analyst‘s hat such as:

• SMEs: You might be a financier who extensively uses Power BI and creates many financial reports; or a human resource expert who creates and supports various HR reports. These people usually fall into one of the Power BI contributor or self-service analyst classifications.
• Data analysts: This is indeed one of the roles that use Power BI the most. The chances are that they are professionals in Power BI development.
• Business analysts: The business analyst role usually has a lot of overlap with data analysts. These two roles normally work closely in a way that the data analysts are more proficient in dealing with the data while business analysts are closer to the business. So depending on the definition of the role, a business analyst can fall into the Power BI developers, Power BI contributors, or self-service analysts classifications.
• Data engineers: The data engineers may interact with Power BI by providing the necessary data infrastructure and ensuring data connectivity. They are responsible for designing, developing, and maintaining the Dataflows and data sources that Power BI relies on. So, depending on their knowledge, the data engineers may fall into the Power BI developer or self-service analysts classifications.
• Data scientists: The data scientists can use Power BI to efficiently integrate their analytical findings into interactive reports and dashboards, enhancing data-driven decision-making, generating insights, and promoting collaboration between data scientists and business users for more informed strategies and solutions. So, the data scientists are mostly classified as self-service analysts.

Indeed, various roles within an organisation can take on the responsibilities of a Power BI developer or analyst, and this adaptability is influenced by the organisation’s specific needs and project demands. Different businesses have different requirements to operate efficiently. So let’s focus on the effects that Microsoft Fabric might have on the so-called “Power BI Developers” and “Analysts”.

How does Microsoft Fabric affect Power BI developers and analysts?

Microsoft Fabric is a new platform that aims to unify the data and analytics capabilities of Microsoft products, such as Power BI, Azure, Dynamics 365, and Office 365. Power BI, on the other hand, is already a popular data platform with a large and diverse user base. We discussed Power BI user classification in the previous section. The classifications correspond to different levels of skills, needs, and responsibilities in the data and analytics domain.

So, depending on user’s roles and the classification they fall into, Microsoft Fabric may affect Power BI developers and analysts in various ways. Here are some possible scenarios:

• Power BI developers: The developers are the users who create advanced reports and dashboards using Power BI Desktop or the Power BI service, as well as custom visuals, templates, and applications using Power BI Embedded or the Power BI API. They may face the most significant changes in their work, as Microsoft Fabric may introduce new development environments, languages, frameworks, and standards for creating data and analytics solutions. They may need to migrate their existing projects to Microsoft Fabric or start from scratch using the new platform. However, it all depends on the project architecture and its demand. As a Power BI developer, you may face no changes in your role at all. A good example is a project that has clear role separation so that the data engineers take care of all data ingestion and transformation using Data Factory and creating Lakehouses. In that case, the chances are that the Power BI developers do not need to be worried about all the data transformation complexities and have to focus on the data modelling and data visualisation sides of things. This by itself can be considered as a good thing or a downside. If you are a professional developer, you might want to know how things are stitched together in the background. If that sounds like you, then buckle up and get ready to learn new languages and technologies.
• Self-service analysts: The self-service analysts may also need to learn new skills and tools to leverage the full potential of Microsoft Fabric. For example, they may need to use Notebooks on top of Lakehouses to access and query the data. Or they may be required to create data transformation pipelines using Dataflows Gen2 and land the data into an Azure SQL Database. One may consider these changes an opportunity to learn more and get proficient in cutting-edge modern technology or find it daunting and limiting.

Conclusion

The transition to Microsoft Fabric may pose some challenges and opportunities for Power BI developers and analysts. However, it is not a reason to fear losing jobs or becoming obsolete. Rather, it is a chance to embrace the new possibilities and innovations that Microsoft Fabric can offer. The key is to stay updated, curious, and adaptable to the changing landscape of data and analytics.