If you are here today, that means that you are somewhere between a stage to prioritize the tool for your Business Intelligence journey among Power BI and Tableau. Transformation of the Business Intelligence operations has never been that easy.
Alright! So, let’s get started and deep dive into the nitty-gritty of the data visualization process and choosing the right tool to solve the purpose.
People think that it’s easy to create the visualizations out of the data that we have on our screens.
Thank you for choosing me to clear the clutter…
There are certain stages through which the raw data has to flow before it is presented to the end user with certain appealing visualizations. Here are those stages:
- Data source selection
- Extract
- Transform
- Load
- Staging
- Semantic Layers, and then comes the
- Data Visualization
Data visualization is an icing on the cake that solicit lot of efforts to create a ‘viz-ready data’.
Without any much fuss let us get started to understand how these two contestants are different…
- Data Processing Capabilities:
Tableau is a “ready to eat” tool that can enhance your data visualization journey. But, it requires a preprocessed data that can be fed to the tool and it can process the data and set appealing visualizations to the canvas.
Tableau provides its separate package- Tableau Prep comprising of : Prep Builder for Combining , shape, and cleaning your data for analysis; and Prep Conductor for scheduling the flow and tracking them for the administered outputs. And here you need a data engineer that can facilitate this experience to a smoother journey.
Yet, this package still lacks the profound integrations of the process and their cohesive experience!!!
Power BI comes as a leader here that takes the data from the raw sources and can process it under its own house of capabilities that comprises of Power Query Editor.
It lets you bring the data from different sources and can cater the information under one roof with the processing capabilities of Microsoft’s star- Excel. It has almost everything that one can imagine modifying with subsequent elevations to the data.
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- Data Modelling Capabilities:
Tableau requires the data to be in a flat structure. Yes, a flat file that includes the data attributes of different table under one frame. Possibly, you are thinking right- as it will make the great use of Join operations. This breaks the tables and make one out of all. Tableau also features advance joining capabilities to allocate collection right information from tables.
Power BI becomes handy when we are required to keep the data to their home tables for referencing and still creating the relationship among different columns of many other tables…
Hurray…
Wait, wait, wait! Not that easy!!!
Do have the deep-rooted understanding of Star Schema? If not, get ready to burn the midnight oil now as star schema is the foundation of data modelling in power BI!
Data modelling is one of the most complex tasks in Power BI that empowers dynamic reporting easy. But one must get their hands dirty to set data flow directions between the tables and restricting the access of the data between the tables.
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- Visualization Capabilities:
Tableau is a great tool in my opinion when it comes to create great visualizations. Though it has limited sets of visualization under its basic frame, it utilizes its capabilities to create advance charts on the canvas.
It proves to be a great tool when you are required to make the visualizations that can please the senses of the stakeholders you are dealing with.
One of the appreciated features of tableau- It suggests you the visualization that can be created once you select the target fields from your data. Yes, it suggests when you select the Dimensions and Measures (data fields, basically) from the data pane.
Power BI has the powers to put the information to the right senses. It provides quite more visualizations that can be a set of your choice including some which are denoted as the advance setup for the Tableau charts.
Those who are familiar with tableau- Dual Axis is the set up that we customize to a chart, while it is a prebuilt widget in the visual set of Power BI.
Power BI has ‘Custom Visuals’ that one can import from the store whenever necessary.
Warning: Do not forget that- These imported custom visuals are gonna impact processing time!
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- User Interface
Yes, I agree! Interface should be my first point to be mentioned!
But I believe that the selection of the tool must not be prioritized on the level of comfort with the interface, but must be considered! The data has the complexities too.
Tableau somewhere is a master in playing the Hide & Seek with you in terms of its interface. It’s not quite intuitive, which makes it a more difficult to use and learn.
Folks with some data analysis experience will have less trouble in transforming data into the visualizations, but those who are just getting their feet wet will likely feel overwhelmed with the uphill battle.
Power BI has a facile interface that relies more on the great drag and drop and intuitive features to help the teams build their visualizations. It’s can be a great addition to any team that seeks data analysis but do not comes from a data family.
Power BI wins for ease of use, but Tableau wins in speed and capabilities.
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- Pricing Model
Tableau has offered bulk purchasing models in its time and now offers subscription model. The current pricing model has the complexities as a tiered system from connections to files to third party applications.
However, if you want direct connections to your third-party apps like Google Analytics, Hadoop, or any Microsoft products, you will need to pay for the Professional edition.
Power BI quotes a lower pricing model that makes it more feasible with a lower price than Tableau with a free version, pocket friendly monthly subscriptions, and a scalable premium version with a higher price.
When it comes to the products like MS Office 365, the way Power BI is set up within the Microsoft ecosystem makes it affordable, especially for those companies who are already deeply invested in Microsoft software.
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Each of the two tools has their own capabilities that makes them different from one another.
But one thing that I admire the most- They both solve the purpose 🙂
Without any superfluous comparisons, let us conclude with the following key take-aways for you:
- Power BI Interface is very easy to learn | Tableau is a quite difficult in terms of learning.
- Power BI is used by both the naive and experienced users |Tableau is used by the analysts and experienced- users mostly use it for their analytics requirements.
- Power BI uses DAX for calculating and measuring the columns | Tableau utilizes MDX for its measures and dimensions. (These are the languages used for additional calculations in data)
- Power BI offers many data points to offer data visualization | Tableau wins in its data visualization capabilities.
- Power BI can handle a quite limited volume of data | Tableau BI can handle a massive volume of data with comparatively better performance.
- Power Bl does not work well with massive amount of data | Tableau works best when there is huge data in the cloud.
I would suggest you making a clever choice between the two tools considering your needs and the ecosystem that your organization is designed in.
Newbies, every journey is engrossing when the roads is new. Get started with any of them. Their community and learning content is enough to have pally terms with the tools. I bet!
The career graph is already set to a bright future independent of any of the two.
Data is everything and the hidden insights will rumble the facts!
All the best for your data journey… 🙂
Addend Analytics is a Microsoft Power BI-partner based in Mumbai, India. Apart from being authorized for Power BI implementations, Addend has successfully executed Power BI projects for 100+ clients across sectors like Financial Services, Banking, Insurance, Retail, Sales, Manufacturing, Real estate, Logistics, and Healthcare in countries like the US, Europe, Switzerland, and Australia. Get a free consultation now by emailing us at kamal.sharma@addendanalytics.com.
Varun Tiwari
Data Analyst
Addend Analytics
