A Comparative Analysis of Data Visualization Tools: Google Data Studio, Power BI, and Tableau
Big data visualization tools are necessary for anyone who wants to create visual representations of analytics to share with others or to better understand analytics. You have a number of data visualization tools to choose from — the problem is, no single tool stands out as the very best for business intelligence (BI). If you research just by looking at product pages, you’ll find that every product claims to be the top solution. Actually, it comes down to what you need.
Having said that, three main options are widely considered to be the best BI visualization tools. These are Google Data Studio, Power BI, and Tableau. We’ll consider each in terms of data manipulation features, usability, integration, and cost to help you figure out which is the right solution for you.
Why Use Data Visualization?
Before you start any analysis of data visualization tools, you need to think about why you want to use such a tool.
Whether you’re an analytics expert or you’re just getting started in the realm of big data, tools like Tableau, Power BI, and Google Data Studio can help you make better decisions. This is because it is difficult for the human mind to grapple with large amounts of data. When the data are presented in visual form, however, you can see patterns.
Plus, when the tool is interactive, you can display the data in a way that makes most sense to your goals. You can discover things like what are the most important factors for conversions, you can make predictions, and you can locate areas that need improving.
With this in mind, let’s begin the BI visualization tools comparison.
Google Data Studio
A top feature of Google Data Studio is its capability to turn raw data into visualizations. Furthermore, a team of developers can work on the same issue in Google Data Studio, just like in Google Docs. Lastly, sharing is just like using Google Drive, including similar access levels.
The main problem with Google Data Studio is its limited capability for rich interactivity. There is no opportunity for users to explore specific parts of visuals or to personalize reports to a great extent. To make matters worse, there are only 50 functions from calculation — fewer than the other data visualization tools. Lastly, Google Data Studio can only work with clean data.
Google data visualization is enhanced by a library of built-in visual types. You choose the type of visual you want, drag and drop it into your report, and add metrics. This sounds simple, but some aspects of Google data visualizations are counterintuitive, especially when it comes to customization and making minor changes to visuals and charts. However, this tends to just be a learning curve. As soon as you’ve got the hang of it, you’ll be able to make attractive reports. Unfortunately, though, you can only use and modify the built-in visuals; you cannot add your own.
For the most part, Google Data Studio does have good usability. Most users will be able to get started immediately. If you already use any other Google Services, it will be even easier, as Data Studio has many of the same UI elements.
Another advantage of using a Google visualization tool is that most Google services are fully integrated. Google Data Studio also supports external connectors like SuperMetrics and Funnel. These allow you to import data from other sources and to blend data in a single table or chart. Bear in mind, though, that such tools can have a hefty price tag.
Google Data Studio is free for unrestricted use. This means that, although it is more limited in some capacities than the other two options, it does have price in its favor.
A major advantage of Power BI is its simplicity to share visualizations, including real-time interactive dashboards. Other features depend on the version. The desktop version has the highest functionality, as it includes tools for data cleansing and normalization.
The main downside is that, on all versions, users have reported performance issues like timeouts and freezes when streaming or importing large data sets.
Power BI data visualization is highly customizable. Like Google Data Studio, it uses the drag-and-drop method for building charts. You can also improve your reports with an expansive library of built-in visuals.
The Power BI interface shares characteristics with other Microsoft products, particularly Excel. This makes it feel instantly familiar to Windows users. Unfortunately, usability can become overly complex when you move beyond the most basic functions — which may be a problem for users who lack experience in Excel.
As the Power BI data visualization tools are produced by Microsoft, there is limited support for Google services. This can be problematic if you are using AdWords. Strangely enough, there is support for Google Analytics.
To overcome integration difficulties, one solution is again to turn to SuperMetrics or a similar service. This will allow you to download data from pretty much any advertising system. You will need to put the data into Google Sheets and then connect Sheets to Power Query. All this is a little more complex than using Google Data Services, but it is still far from impossible.
As for other data sources, Power BI supports many, including Salesforce, Facebook, SQL databases, SAP, and, of course, Microsoft Analysis Services. In addition, you can use stored files on your computer, accessing them with the Power BI Personal Gateway.
There are two versions of Power BI: a free one and an enterprise one.
The free version gives you access to the basic features, allowing you to try out the tool before purchasing. It gives you 1 GB of data and 10K rows per hour of streaming data for all your dashboards and reports. There are some restrictions with data refreshing and collaborations.
The enterprise version is called Power BI Pro. For $9.99 per user per month, you receive access to all services. Plus, your data limit increases to 10 GB per user and you gain 1M rows per hour of streaming data. Other additional features include direct connection to data sources and on-premise data through the use of Data Connectivity Gateway as well as advanced collaboration tools.
Now we come to the last of our data visualization tools: Tableau. Two main features make Tableau stand out — built-in data blending and real-time collaboration. The latter feature comes with a number of ways to share reports, which consist of publishing to a Tableau server, publishing a Tableau workbook, and sending the report in an email.
Another selling point of Tableau is the flexibility of its dashboards. You have the freedom to change the layout of your dashboard, even adding overlaps.
All this isn’t to say that Tableau is free from disadvantages. For example, although features are supposed to be for broad use, they can feel specialized and restrictive. Furthermore, Tableau does require you to carry out initial data preparation.
Tableau offers unique ways to display analytics that are not present in any other data analysis visualization tools. For instance, it allows you to create visualizations called “word clouds” and “bubble charts” — this second option presents elements of categorical data. Both of these visualizations enhance comprehension by drawing attention to the most relevant aspects, which is extra important for sharing purposes.
Easy to use, Tableau is suitable for any type of user. It is intuitive enough for those with no prior experience in data visualization but also comprehensive enough for developers. The interface is especially well designed — you can get anywhere in no more than two clicks. It is also obvious where to find and how to use all the features. When you do need extra support, you can turn to a variety of resources, such as tutorial videos, blog articles, social media posts, and forums.
You can connect Tableau to more than 30 different data source types, including data systems organized in file formats, relational and non-relational data systems, and cloud systems.
There are three options to use Tableau: Desktop, Online, and Server.
Tableau Desktop is available for individuals at $999 per year and for enterprises at $1,999 per year. Personal use provides you with six data sources, whereas the enterprise version gives you 44 data sources. Both come with customer support.
Tableau Online is a cloud-based service. The public option provides you with free online visualization tools. However, the downside is that all your reports will be available publicly. There is also a private online version, which costs $500 per year per user.
Tableau Server is the best option if you need a solution for your entire business and you want complete control over your data. You’ll need to operate your own server and have the infrastructure to manage security. The tool costs $10,000 for every 10 users. If you want customer support, it will cost you 25 percent of the total annual cost. The main disadvantage of Tableau Server is that it has no concept of versioning. Plus, you will need some IT consultancy.
Data visualization tools like Tableau, Google Data Studio, and Power BI all enhance your capability to display and examine analytics. The right one for you will depend on what you’re looking for in a tool — in terms of integration, usability, and features as well as whether you prefer open source data visualization tools. Consider what are your requirements now and how your team may change in the future to avoid the need to transition to a completely different tool later.
Originally published at https://insightwhale.com on November 19, 2018.