What is better, Power BI or Tableau?

The 6 core factors that will make it easy for you to choose the best tool.

Chaya Chaudhari
Globant
8 min readJan 24, 2022

--

It’s important to have access to the right tools when working with data. The right tool will help with many Business Intelligence(BI) activities. Activities such as extracting valuable insights, creating visual representations, and analyzing data. Having said that, there are many platforms and BI tools available today. Based on your needs, choosing the right tool is critical. I have explained 6 factors for you to make an informed decision. In addition, this article will give you a basic understanding of Power BI and Tableau.

Selecting a BI tool: Factors you need to consider

Analysts can use BI tools to generate reports, visualizations, and insights. BI tools offer data-related activities like getting data from different sources, preparing it for analysis, and creating graphs. There are many BI tools available. To arrive at the best tool, let’s focus on the core factors.

Fig 1. Core Factors

Let’s examine each factor in more detail.

  • Pricing
    Besides the following attributes, When picking tools, this attribute is crucial. Consider this before will help with the planning of budget for a project.
  • Ease of use and learning
    The ease of use depends on the people who plan to use the BI tool. Some tools need technical expertise, while others do not. If you intend to use the tool for data analysts, it is well understood that the analysts will have technical expertise. Some tools come with an intuitive interface. It is very helpful for non-technical users.
  • Cross-platform compatibility
    Cross-platform compatibility means the ability to function on one or more software platforms.
  • Tabular Representation
    It is a systematic arrangement of data in rows and columns. For the data analysis, some users consider tabular representation. Hence knowing the limitations help the users to choose the tool.
  • Auto-refresh of the report
    Once you create the reports and visuals on the initial datasets, this factor becomes relevant. If the underlying data updates we need to refresh the report built on top of it as well. Having the auto-refresh capability reduces the manual efforts for the users.
  • Performance
    Report generation, visualizations, and data analysis speed vary between tools. For some tools, the performance is good for smaller amounts of data, but for large amounts of data, it may be too slow. Based on the use case you need to decide on the tool.

Now let’s understand the fundamentals of both BI tools.

Power BI

Power BI is a data visualization and analytics tool. It can handle data from various sources and allows the creation of ad hoc reports and dashboards. It makes use of SQL which is an advantage for many analysts. Drag and drop capabilities and many connectors make it easy to use. Below is a diagram showing the basic components in Power BI.

Fig 2: Basic Components of Power BI

Following is a list of Power BI’s basic components with details.

  • Dashboard
    Dashboards are Canvas in which you can create visualizations. These visualizations are tiles. Selecting a tile redirects you to the report. The best practice is to include only the most important elements of the use case on the dashboard. The below image shows the dashboard having 3 tiles.
Fig.3: Sample of Dashboard
  • Report
    The report is a visual representation of data analysis. The user decides the number of visualization in the report. The report refresh occurs when there is a change in the backend data.
  • Workbook
    Workbooks are Excel files. You can browse the data in workbooks as you would a spreadsheet. Else, you can convert the data into datasets, which you can use to create reports. For the companies that rely on Excel for most of their reporting, a workbook like Excel is beneficial.
  • Datasets
    Power BI datasets contain the data imported into the platform. To start building reports one needs all the data in one place. This is what Power BI does using datasets. A dataset can be part of many reports. These datasets are core parts of Power BI. They are data-ready. It means you can use them to create reports and visualizations.

Products

Let’s learn about the various products offered by Power BI.

  • Power BI Desktop: This is an application that is free to download. It is useful for the following tasks
    a. To connect to various data sources using the query editor
    b. To transform, shape, and model the source data into datasets. Used for analysis, visualizations, and reports
    This is a complete tool to achieve the greatest efficiency in BI
  • Power BI Service
    Power BI Service falls under the software as a service. It is beneficial in collaborating, sharing, and distributing the reports. Besides analyzing datasets and creating reports, Power BI Service provides limited modeling functionality.
  • Power BI Mobile
    Power BI offers this service for various platforms like iOS, Android, and Windows. You can use it for connecting with your cloud data or on-premise data. This platform allows you to view and interact with reports and dashboards.
  • Power BI Report Builder
    This is a service provided by Power BI for the creation of paginated reports. It is a detailed report definition. It consists of which data is being used for the report creation and how you plan to display it. when you start the report execution, the report builder’s job is to execute the definition.
  • Power BI Report Server
    It is an on-premise report server with a web portal. You can say the Power BI service is a superset to the Power BI report server. Please refer to the link for more details. https://docs.microsoft.com/en-us/power-bi/report-server/compare-report-server-service
  • Power BI Embedded
    This is another premium service. It helps stakeholders to embed reports, dashboards, and tiles, in a web application or on a website

Now let’s take a look at Tableau.

Tableau

Tableau is a BI tool. It helps users create effective dashboards and visualizations. It comes with the Ask Data Feature. Which provides users with relevant results based on automatic data visualization. Below is a diagram showing the basic components in Tableau.

Fig 4. Basic Components of Tableau

Following is a list of Tableau’s basic components with details.

  • Dashboards
    Dashboards are collections of a set of views. The views are reports. The user classifies the reports according to the use case. For example, if you have created a dashboard for reviews of market trends of various brands. All the brands will have a separate view on the dashboard making it very easy for reviewing.
  • Worksheet
    The worksheet consists of a single view. It can include various cards and shelves. It consists of a high-level view of the visualizations.
  • Cards and Shelves
    The worksheet consists of Card and Shelves. They are rows, columns, filers of the dataset. These components help drill down the data and arrange it per the reporting need.
  • Story
    The story is a series of dashboards that together convey in-depth knowledge of the data. You can begin with a conclusion and then lead the user through the different data points. Alternately, begin with presenting data points and end with a conclusion.
Fig 5: Sample Story

Products

Let’s learn about the various products offered by Tableau.

  • Tableau Prep
    This product facilitates data prep automation. Also, helps in combining and cleaning data. This in turn will make the visualization process fast.
  • Tableau Desktop
    It is a data visualization software offered by Tableau. It helps transform statistical data into visual representations like graphs and charts. Provides users with business insights due to various data exploration abilities. You can share the workbooks created locally. but the recipient needs to have the Tableau desktop installed. It is most useful for developers for creating reports. It also helps in providing valuable insights to decision-makers.
  • Tableau Server
    Its basic functionality is to share the data insights created using Tableau desktop. It is an administrative service provided by Tableau. It enables control over the content shared via the Tableau server. Tableau server is the best platform for decision-makers.
  • Tableau Online
    It is a SaaS service for Tableau. It comes with a data connection option for Amazon Redshift, Google BigQuery. You can use the Tableau ID to authenticate users. Once authenticated, users can access views and dashboards published to Tableau Online. Still, editing has its limitations. As an example, its limitation is to certain rows rather than the entire dataset. Also, you need to have the server data connection before editing can begin.
  • Tableau Mobile
    You need a Tableau Online or Tableau Server account to use the Tableau Mobile app. You can visualize your data in no time with Tableau Mobile. It is one of the fastest methods of presenting your data. In other words, you can explore and share content with your users or stakeholders.

How to choose between Power BI and Tableau?

We have covered the basics of Power BI and Tableau. Let’s now relate the core factors with both the tools. Tableau is relatively more expensive than Power BI. For Instance, consider the basic versions of both tools. Power BI costs $9.99 per month and Tableau costs $70 per month. If the stakeholders are non-technical, Power BI offers an intuitive interface that makes it easy to use. Tableau is the most suitable option for technically sound users. Power BI does not support iOS. Tableau is available for both Windows as well as iOS. Tabular representation has a limitation of up to 16 columns in Tableau. It might be difficult to represent large amounts of data in the form of a table. On the contrary, Power BI does not have any restrictions of this kind. We have the auto-refresh functionality in Power BI. The Auto-refresh option is unavailable in Tableau. We have to manually perform a refresh on the reports. Tableau can generate visualizations even with a large volume of data within no time. Power BI is slow when dealing with large datasets. Thus, the choice of tool should be determined by the individual requirements and by the core factors (Fig. 1).

--

--