The four Power BI roles

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#Powerbi users can actually be divided into four different roles. Read all about it in this article.


When talking about "the Power BI user," I find it useful to distinguish between four different kind of users. They all need a different approach when it comes to training, guidance, software and licenses. For the PL-300 (Power BI) exam, candidates are to distinguish between different roles like so:

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And that makes total sense when looking at the bigger picture of data management within an organization, which goes well beyond Power BI and also includes Database Management, Data Science, Azure Synapse and more.

The four roles

I would like to propose, however, a distinction between the professionals that use Power BI.

1 The Power BI Engineer

This is the individual who performs the ETL (Extract-Transform-Load) and designs and develops the dataset, including DAX measures. This is a highly technical role as it involves connecting to all kinds of source systems. That includes using all of the out-of-the-box connectors but might also involve connecting to different sources through an API or otherwise. Also, when more exotic transformations on the data are required that aren't supported by Power Query's User Interface, writing the M code to perform these transformations is part of the role of the Engineer.

The Power BI dataset can best be modeled in a dimensional structure. This requires that the engineer has sufficient theoretical knowledge of and experience with dividing the world of data between facts and dimensions in all sort of scenarios. Also, writing DAX code in order to produce the required measures is something that requires sufficient knowledge and experience.

The output of the work of the Engineer is a dataset that serves as input to the data analyst.

2 The Data Analyst

The Data Analyst is the individual that takes the dataset developed by the engineer as input and explores and analyzes the data within it. An analyst would do so by by slicing and dicing the quantitative data in the fact tables by applying filters on the dimension tables. This allows for all sorts of insights into the data. Also, Power BI assists in data analysis by providing for Artificial Intelligence trough a number of AI visuals.

The goal of the data analyst is to find hidden insights into the data that will tell the story behind the numbers of an organization.

In order to communicate these insights, a data analyst requires strong data visualization skills. Ensuring that the information presented on the report effectively satisfies the Report Users information requirements, choosing the right visuals and ensuring effective distribution in the Power BI Service are all part of the job.

The output of the Data Analyst is a report that serves as input to the Report User.

3 Report User

The Report User is an individual with business responsibility and wants to base decisions upon facts rather than then assumptions. Therefore, the Report Users takes the Power BI report as input and bases business decisions upon the information presented on it. A Report User shouldn't require a background in data analysis as a Power BI report should be tailored to the Report User. All that is required is some end user training which shouldn't take more than a few hours max. Drilling down, up, through, hovering over visuals and setting slicers are all relatively easy to do for the Report User.

4 Power BI Admin

Last but certainly not least is the Power BI admin governing the usage of Power BI within an organization. This is the individual that is in control over all tenant level Power BI settings, creation of workspaces and apps, access management and more. Depending upon the size of an organization, the centralized Power BI responsibilities can grow to also include production of central datasets, establishing a Power BI Community, Center of Excellence, setting up a help desk and more.

Roles might differ based on the size of an organization

For small organizations that just start out using Power BI, it is usually done by one enthusiastic individual. In such a scenario, obviously, the above distinction is not yet made and that individual will probably assume the responsibility for all four roles without being conscious of it. As organizations grow, Report Users within the business will start relying upon analysts to produce reports for them. However, it is rather common for the role of the engineer and data analyst to be performed by the same individual, also in larger organizations. Without being consciously aware, though, these individuals do assume responsibility for both roles and therefore need to be capable of both. Only in large organizations have I encountered scenarios where engineers produce and publish a dataset without a report on top of it in order to allow for data analysts to use it as input for their job. The role of the Power BI admin also will grow and become more mature along with the size of an organization and the degree to which Power BI is being used.