Tableau vs Google Data Studio: A Comprehensive Comparative Analysis

on BI Tool • July 17th, 2020 • Write for Hevo

Introduction

Business intelligence tools are a critical part of deriving actionable insights from an organization’s customer data. These tools help analysts dig deep into data, explore, visualize, and make it available in a form that is suitable for the higher management to take path changing decisions. Such tools help in building custom dashboards and reports without needing any coding effort. They also enable the reports to be scheduled for specific times and audiences.

All these functionalities need them to be constantly connected to various databases and query them. This means connectivity support for various databases and data manipulation capability becomes a big factor assessing business intelligence tools.

In this post, we compare two of the most popular business intelligence tools – Tableau vs Google Data Studio.

Tableau – Features

Tableau started as a desktop-based application but now supports a cloud-based hosted experience also. It can be used to create custom dashboards and it excels in the ability to do deeper exploratory analysis on data. It provides connectors for a large number of data sources and supports live connection for most of them. Tableau supports transforming data through its own module called Tableau prep which is bundled along with the creator license. 

Google Data Studio – Features

Google Data Studio is a completely cloud-based offering that helps users create dashboards and reports by connecting to a number of data sources. Being a Google product, it provides comprehensive support for most Google offerings like Google Analytics and Google BigQuery. It inherits the sharing abilities of typical Google products and hence supports the easy sharing of reports and dashboards with other users. Other than the cloud-based data sources, it also supports popular on-premise data sources like MySQL. 

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Tableau vs Google Data Studio

Now that we have a basic understanding of the capabilities of both of these tools, let us dig deeper and find out how these tools fare with respect to the typical factors based on which business intelligence tools are assessed. 

The comparison between Tableau and Google Data Studio will be on the following parameters:

  • Installation Methodology – On-premise vs cloud-based
  • Data Exploration and Data Interactivity
  • Learning Curve/Ease of Development
  • Database Connector Support
  • Collaboration Features
  • Pricing
  • Transformation
  • Support for Real-time Updates

Installation Methodology – On-premise vs cloud-based

As mentioned above, Tableau supports both kinds of installation. It can be installed as part of an on-premise server and development can be done on the Tableau desktop application. For cloud-savvy users, it also provides the flexibility of a completely managed hosted environment.

Google Data Studio is a completely cloud-based offering and your data will reach Google cloud when you use it. Organizations with strong data security principles and mandates of keeping data on their own premise are better off with Tableau for this reason alone. 

Data Exploration and Data Interactivity

Both tools enable analysts to explore data through their interface and interact with it. Tableau provides a richer set of exploration and charting tools when compared to Google Data Studio. In this space, if you need to interact with your data using complex functions, Tableau has an advantage. Tableau supports deeper interactivity while creating reports. Both these features need expert developers to exploit it though. That takes us to the learning curve involved in using these tools

Learning Curve/Ease of Development

Google Data Studio supports a much lesser level of complex functions and interactions. This means the learning curve is less steep when compared to Tableau and this is a big advantage for organizations that need to set up simple dashboards and reports quickly.

The Tableau learning curve is steeper and requires expert analysts to exploit to its full potential.

Database Connector Support

Data Studio closely integrates with all Google software like BigQuery, Google Analytics, Firebase, etc. Native support for other cloud-based data sources is limited in the case of Google Data Studio. The same is the case with most file-based data sources. For example, Google Data Studio still does not natively support excel files. The only way to use them is to convert to CSV or a Google Sheet document. Google allows community connectors to be developed for Data Studio through its partner program. Most of them are paid utilities. 

Tableau, on the other hand, offers great support for most databases, file-based formats as well as cloud-based data sources like Salesforce natively. 

Collaboration Features

Data Studio inherits the access control and sharing capabilities of typical Google products and thus provides a very easy to use granular sharing ability.

Tableau also provides sharing ability through its server, but it is not as intuitive as Google’s simple implementation. But with respect to functionality both of them are equally placed in this regard. 

Pricing 

Google Data Studio is now offered free along with the Google Cloud Platform.

Tableau is offered based on licenses and starts from $15 per month viewer license and $70 per month for the creator license. Each deployment will require at least one creator license. 

Transformation

Tableau provides an add on a tool called Tableau Prep with its creator license. Tableau prep is to be used for all transformation requirements before dashboards and reports.

Google offers limited transformation abilities. The only meaningful transform possible is the JOIN operation that can be used to combine data from various sources. So in the case of transformation, Tableau is certainly more feature-rich than Data Studio. 

Support for Real-time Updates

Both Tableau and Google Data Studio support real-time updates for specific data sources based on databases or APIs. For static file-based data sources, manual refreshes are needed in the case of Google Data Studio. Some custom coding using app scripts can mitigate the need to manually refresh. Tableau allows for scheduled extracts in such cases and provides near real-time updated dashboards and reports. This gives Tableau an edge over Google Sheets in case of real-time ETL outside of the Google app ecosystem.

When to Use Google Data Studio

Summarizing the above facts, Google Data Studio may be a good fit for your organization, if your use case satisfies most of the below conditions:

  • You want to set up a simple dashboard based on limited data sources quickly.
  • Your development stack is primarily based on Google tools. 
  • You do not need complex transformations before reporting on the data. 
  • Your architecture is primarily cloud-based and you do not mind your data being taken outside your premise. 

When to Use Tableau

It may be worthwhile for you to consider Tableau if you requirement fits into most conditions listed below:

  • Your architecture uses multiple kinds of on-premise and cloud-based data sources and most of them are outside the Google ecosystem.
  • You require complex transformation support
  • You have a dedicated business analysis team and can exploit the advanced features of Tableau.
  • You do not mind spending on business intelligence software and are open to paying for license fees per user.

Conclusion

Both Tableau and Google Data Studio can support most standard business intelligence use cases, but differ when it comes to the kind of supported data sources, the extent of transformations, and the learning curve involved.

To conclude, Google Data Studio is a much more slick and user-friendly tool that looks and feels aesthetically modern in every way. It is also free and hence for many small and medium scale companies, Google Data Studio is a boon.

But if you are a large enterprise with no human resource or budget constraints and you need to work with complex data, then Tableau should work well for you.

In the case of both the tools, database connector support is still not comprehensive enough and lacks native support for many cloud-based services.

Using a cloud-based ETL tool like Hevo can mitigate this lack of connector support. Hevo supports connections with most data sources to both of these tools and provides a completely code-free experience.

Hevo supports rich transformations on the fly and allows your analysts to focus only on the analysis part rather than writing code. 

If you are interested, you can try Hevo for free here!

Share your thoughts in the comments below! What do you like better- Tableau or Google Data Studio?

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