Power BI vs Tableau
When it comes to data visualization platforms, there are numerous options available on the market. As the value of data moves to the forefront of the business community’s mind, and analytics are increasingly relied on for decision making within organizations, there will be an even greater amount of platform options.
However, at Untitled we typically default to two specific platforms that stand a head above the rest. Tableau and Microsoft’s PowerBI are go-to platforms in the Untitled Tool Kit, especially when it comes to proof of concept projects we conduct for our clients. Many organization’s decision makers and businesses have never seen the data they collect visualized in a meaningful way.
Good data visualization techniques lead to a better grasp of complex information concepts, and that’s why we always advocate that either one of these platforms be a part of most of the projects we do.
This is not an affiliate post attempting to convince you to lean towards one platform over another. This is simply an informative post to help you decide on which platform will be best suited for your projects needs. Additionally, we hope that anyone reading this post who would like to utilize these tools for a project with us, please reach out through the contact form.
When it comes to picking which platform you will utilize for your next data project, we see that the decision boils down to four primary categories. The four categories are compatibility, the user learning curve, customization options, and cost.
Compatibility
Compatibility is a key driver for picking which platform will work best for your organization. This decision also boils down to which technology stack your company is currently leveraging, as each platform has different specifications regarding the types of data sets and databases the product is compatible with.
One of the big advantages of Tableau in this category is that if your company is leveraging AWS in their stack, the platform is configured to connect through a Tableau Server on an Amazon Elastic Compute Cloud. Most of the companies that we work with have migrated their data to the AWS cloud, or are in the planning process doing so. If the data project you are conducting will be for a company utilizing AWS, then Tableau will probably be the best option.
Our Choice:
PowerBi is “compatible” with AWS Redshift, but from our experience this tends to be a tedious set up process, and given that Microsoft has historically not played nice with Amazon in the cloud computing and data warehouse industry (as they are competitors), we don’t expect for that pipe to be well supported. Another point to consider is if your company, and specifically database and analytics team fall into a more open source code stack as well, they will definitely have a preface towards Tableau.
On the other hand if your company is heavily leveraging a Microsoft stack, then PowerBI is the obvious solution. Given that PowerBi was originally designed to be a business intelligence tool extending from Excel and the Azure Cloud Computing service and data warehouse offering, this tool integrates seamlessly being a part of the Microsoft family of products.
For a full list of Tableau supported data sources, visit this link. For a full list of PowerBi supported data sources, check out this link.
Our Choice:
Learning Curve
An important element to consider is the learning curve element that’s a factor both for you and who else you expect to utilize this tool for decision making. The latter part of that sentence (italicized for a reason) is way more critical. A point to make is that if you are diving into a new platform for the first time, learning it in order to produce the best model for stakeholders is important. However, unless you want to be constantly on-call to support every component of it, choosing an option that will be easiest to grasp by your end user outweighs however arduous it will be for you to pick up a new tool.
For this category, we tend to push clients towards PowerBi. Again, because this product is from the Microsoft suite, we see users of Office365 get comfortable with the platform, and how to understand the information being displayed to them rather quickly. From the standpoint of acquiring a new tool for your own tool box, we found PowerBi much easier to learn then Tableau.
Customization
With the previous paragraph in mind, Tableau has a more robust set of capabilities and a longer shelf life of over 10 years comparatively to PowerBI. This means that the platform is more built out, with a hardy tool box to assist you with cleaning, modeling and visualizing data. Within the category of customization, the Untitled team will weigh in favor of Tableau.
Tableau offers a myriad of visualization options and has a much more lengthy list of data source compatibility as well, allowing you to tailor a solution specific to the needs of your data pipeline.
Our Choice:
Our Choice:
Cost
Cost is pretty straight forward and contingent upon the first three categories mentioned in this article. If one platform is much more suitable to the challenges you are trying to solve, then don’t pick one platform over another just because of cost. We assure you that picking the right tool for solving a problem will pay dividends.
With that said, PowerBi is free to start, with a $9.99 a month per user for pro edition (well worth it), with enterprise options also available. Tableau comes with a free 14 day trial, which upon expiration will assume a $70 a month per individual user pricing option. Additionally, Tableau offers a “Teams and Organizations” (the equivalent of PowerBI’s enterprise edition) option with tiered pricing per user option based upon individual user needs.
As stated in the beginning of the article, this post was not written to sway you one way or another, but rather to help you pick the best solution for your organization’s needs: Power BI vs Tableau
If you would like to start a project with Untitled leveraging one (or both) of these powerful software solutions, please reach out to us through the contact form. We are ready to take on any data driven marketing projects you and your team may have!
