With the rise in importance of using data for business growth in recent years, business intelligence (BI) platforms have become one of the hot topics in the data analytics world. Your data pipeline will be incomplete if there is no BI platform at the end to visualize the data and help you tell compelling stories. If you are an analyst, a data scientist in charge of data execution or you are a CTO or head of data in charge of strategies and you are contemplating whether to adapt Tableau or Power BI, this article aims to provide you with everything you possibly need to know to make an informed decision.
Before you decide on any BI tool, you should be aware of all your options. Here are a few other comparison posts we’ve written to help you make a decision:
- Top Power BI Alternatives
- Top 5 Self-Service Reporting Tools: An In-depth Review
- Top 4 Metabase Alternatives
- Top 5 Google Data Studio Alternatives
Tableau vs Power BI High Level Comparison
Tableau and Power BI both are among the most popular BI platforms in the market and as much as they share some similarities, they have major differences as well. Power BI uses DAX (Data Analysis Expression) as its main language to model and manipulate data. If you are proficient in Excel, you won’t have much trouble adapting to Power BI. On the other hand, Tableau has a unique interface and it is more focused on visualization rather than modeling. Tableau has its own visual query language called VizQL. This might make it a bit difficult for new users to pick up Tableau as they need time to get familiar with the interface and the query language.
In terms of similarities, both platforms can connect to various data sources and they both have built-in machine learning (ML) capabilities which help users understand the trends and patterns of data. Power BI leverages Microsoft Azure to analyse data and Tableau has Python ML capacities for ML operations over data sets.
The following sections will provide you a Tableau vs Power BI comparison in a detailed level.
Tableau VS Power BI: Feature Comparison Table
Related reading: BI Tools Comparison Matrix: A Holistic Collection (Updated)
1. Power BI VS Tableau Cost
When comparing any BI platforms, cost is one the main elements that comes to mind. Ideally you want to choose the most affordable platform that fulfills your requirements in the most efficient and effective way possible.
Power BI premium costs you USD $20 per user per month while Tableau Creator costs you USD $70 per user per month. Power BI has an enterprise-level pricing for USD $4,995 per capacity per month as well. This solution offers unlimited users and autoscaling with Azure subscription to automatically scale Power BI Premium capacity.
Easy deployment is one of the key considerations when it comes to Microsoft Power BI vs Tableau comparison. Here is the interesting part. Tableau allows you to run it on your existing infrastructure be it Linux, Windows, Public Cloud or on-premise whereas with Power BI you are required to migrate to Azure. This might cause inconvenience to companies that use other services such as GCP or AWS. If you want to deploy Power BI on-premise, you’d need Data Gateways which function as a link between Power BI service and on-premise data sources.
3. Data Source Integration
Many companies use different means and platforms to store their data. In a company different departments might store data across Google Cloud Bucket, BigQuery, Amazon Redshift and even CSV Files. So it is crucial that you choose a BI platform that supports as many data sources as possible. The good news is that both Tableau and Power BI support connecting to multiple data sources. The table below compares the data source integration capability of the two platforms for some major data sources:
The table above does not cover all the data sources that each platform supports and it only highlights the popular ones. As you can see most of the main data lakes and storages are supported by both platforms. Just take note that for Power BI, connection to some of the data sources require Data Gateways.
4. Data Modelling
When it comes to data modelling, you want to know how you can define relationships and join tables using multiple dimensions to craft the most compelling insights. Let’s look at some of the main modelling capabilities for Tableau and Power B analyzed by David Eldersveld:
- Logical Data Model
Both Tableau and Power BI use a logical data model approach. This has been a core layer of Power BI since its creation but it is relatively new in Tableau. This is how it looks like in both platforms:
Power BI (https://dataveld.com/)
- Multiple Fact Tables with More Than One Dimension
Power BI strongly supports data models that are based on multiple fact tables with multiple dimensions while in Tableau building multiple fact tables with more than one dimension is not supported.
- Using Multiple Fields to Define Relationships
In this aspect Tableau offers a competitive advantage. With Tableau you can use multiple fields to define relationships while with Power BI you can only use a single field to define relationships. The work around to define relationships based on multiple fields in Power BI is to build a single key by concatenating the fields.
- Active and Inactive Relationships
Single active relationships between tables is supported in both Power BI and Tableau. Additionally, multiple inactive relationships between the same tables are allowed in Power BI as well. Using DAX, data modelers can define measures to use inactive relationships and replace default active relationships.
5. Power BI VS Tableau Visualization
Visualization helps you make sense of data and like any other tool, some are tailored for specific use cases and some can be used in more generalized manners. In order to choose the right visualization for your data, you need to consider 3 criteria:
- The goal of your visualization
- Type of data you want to display
- What your audiences want to know
Both Power BI and Tableau allow users to visualize data using different templates and formats. In this section we are going to highlight some of the visualization options available in both Tableau and Power BI.
In general, Visualizations in Tableau and Power BI are divided into 3 main groups:
Charts: Charts contain graphs, plots and some diagrams that are focused on quantitative data that can be mapped to coordinates. Some of the main types of charts available in Tableau are bar chart, line graph, dual axis chart, grant chart, etc.
Geospatial: Geospatial visualizations allow users to illustrate the relationship between various points on the map using marks, line and colors.There are varieties of geospatial available in Tableau including proportional symbol maps, heat maps, flow maps, cartogram and many more.
Tables: Tables are most suited to depict data in a two axis matrix and are normally in a spreadsheet format. In Tableau there are types of tables available namely crosstab, heat map and highlight table. In an article published in Chartio in October 2020, Matt David states that a good data visualization should have 4 main characteristics:
- Accurate: The visuals used should accurately display the data and its trends.
- Clear: It should be easy to understand for audiences.
- Empowering: It should contain actionable insight to enable users to take action after looking at the visuals.
- Succinct: The data displayed should not take long to resonate with audiences
Who is the winner — Power BI or Tableau?
We’ve gone through many aspects of Power BI and Tableau comparison and highlighted features and capabilities that each platform has to offer including pricing, deployment, integration, data modelling and visualization. The truth is there is no absolute winner when we compare Tableau and PowerBI. Your choice of a BI platform completely depends on the budget and requirements that you need to fulfill in order to deliver the job as efficiently and effectively as possible. Of course, the areas covered in this article are the crucial part of your decision making criteria.
If you are still stuck and can’t decide whether to go for Tableau or PowerBI, my suggestion is to try both. Both Power BI and Tableau offer free trials. Free trials are the perfect opportunity for you to try out the features, integrations and visualization capabilities and make an informed decision based on your evaluation and experience.
Frequently Asked Questions
Which free version to choose — Tableau Public VS Power BI Desktop?
Power BI Desktop is a free version of Power BI that you can install on your computer. Using Power BI Desktop you can connect to multiple data sources to transform and visualize your data. Once the visualization is done, users can share the reports with others using Power BI Service.
Tableau Public is a free version of Tableau that allows users to explore and visualize data and then share it publicly with Tableau Public community online. With Tableau Public, you can share your data story with the world. Once you save your work to Tableau Public, it may be shared by sending people the link to the visualization’s homepage, via email, twitter, facebook etc. You can also embed it in your own website.
To conclude, both Tableau Public and Power BI Desktop are free for users to explore and visualize data; however, your data with Tableau Public is not private and is shared with everyone in the community. So if you don’t want anyone to access your visualization reports, go for Power BI Desktop.
Tableau VS Power BI: Sharing Capabilities?
Despite their differences, Tableau and Power BI share many capabilities too. Let's look at their major common features below:
- Comes with free and paid version
- Can be deployed on various environments
- Can connect to many data sources
- Support SQL
- Data modelling options
- Have variety of visualization templates
Tableau Calculated Field vs Power BI DAX?
Calculated fields are the data analyst’s favourite as it allows them to create new data using the existing metrics in the data source. The good news is that both Tableau and Power BI have the calculated field feature.
In Tableau it is called calculated fields and you have the option to create basic calculations, level of detail expression (LOD) and table calculations. When you create a calculated field in Tableau, it is added to your existing fields in the data source.
In Power BI calculated fields are called calculated columns and it is created using a DAX formula. Additionally, Power BI offers calculated measures as well. The difference between these 2 is that calculated columns are added as additional columns with values for every row whereas measures are aggregated expressions based on multiple rows in a table or in many tables.
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