Data visualization tools like Tableau Desktop and Power BI have become indispensable for businesses and data professionals seeking to gain insights from their data. Both of these platforms offer powerful features for creating interactive and informative visualizations. However, they often approach the same concepts differently, which can be a bit confusing for users who are familiar with one but new to the other. In this blog post, we’ll explore some of the most important concepts that exist in both Tableau and Power BI, highlighting their similarities and differences.

This blog series is split into different parts. In this part, the concepts mentioned will be Data Sources, Data Preparation, and Visualisations. For each of the core concepts, a short description will be given of how they are done in both Tableau and Power BI as well as a short video demonstrating the concept.

Data Sources


In Tableau, data connections are created using the home page with the connect pane on the left side. Making a connection will shoot you to the “Data Source” tab where the data model can be edited. Users can connect to various data sources, such as databases, spreadsheets, and web services, and start building their visualizations from there.

Power BI:

Power BI uses the “Get Data” feature, accessible from the top ribbon on the main page. Which allows users to connect to data from different sources. It provides a similar range of connectivity options as Tableau.


While the data source connectivity is similar in both tools, the user interface for setting up connections and transformations may vary. Tableau’s interface is more streamlined, while Power BI offers more advanced data preparation capabilities through “Transform Data”. However, the connection process with Power BI all happens within the main report page.

Data Preparation


Tableau’s data preparation features are primarily found in the “Data Source” tab, where you can perform data cleansing, transformations, and calculations. As well as bring other tables to form relationships between them.

Power BI:

Power BI offers data preparation through the Power Query Editor, a separate application within the Power BI suite. It provides a visual interface for data cleaning, transformation, and enrichment.


The main difference is the separation of the data preparation tool in Power BI, making it more robust and user-friendly to Excel users. Tableau users may need to use additional tools like Tableau Prep for more complex data transformations. Power Query offers a wide range of transformation possibilities with its interface quite loaded.



Tableau offers a wide variety of charts, graphs, and dashboards, allowing users to create rich, interactive visualizations with ease. You can drag and drop fields onto the canvas to create visualizations. The visualizations will be automatically built on what type of fields are put in which sections of the canvas. The properties of the visualization can be edited afterward.

Power BI:

Power BI offers similar visualizations but uses the “Visualisations” pane for creating visuals. Users can drag and drop fields onto predefined visualization types or check the fields from the data pane. The type of visualization is determined before the fields are used. Meanwhile, in Tableau, this is usually the other way around.


The difference lies in the user interface and the available options for custom visuals. Tableau may offer a more intuitive drag-and-drop experience, while Power BI extends customization possibilities through the marketplace. One of the other main differences between the two is that with Tableau, there are a lot of possibilities when it comes to the more unconventional visual building. Or the possibility of creating visuals that do not necessarily “come out of the box”. With Power BI, there is a lot more selection in the type of charts you can make, however, it is much more difficult to create visuals that do not come out of the box.

Final Remarks

Tableau and Power BI are two of the most popular data visualization tools, each with its unique strengths and features. While they share many core concepts, the way these concepts are implemented can differ. Understanding these similarities and differences is crucial for users who switch between the two platforms or work in organizations that use both. By recognizing these distinctions, data professionals can effectively leverage the capabilities of both Tableau and Power BI to create impactful data visualizations and gain deeper insights from their data.

Thank you for reading this blog. Also check out our other blogs page to view more blogs on Tableau, Alteryx, and Snowflake here.

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