Q 424. How does the data visualization tool Power BI compare with Tableau? Provide use cases that highlight advantages of one over the other.

 

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Below is the comparison study between Power BI and Tableau.

Tableau	Power BI
Can handle large volumes of data.	Can handle only limited amount of data.
Excellent customer support.	Only paid version has good customer support.
Works best with large data sets kept in cloud.	Does not work well with large amount of data.
Experienced people uses Tableau the most	Used by both naïve and experienced professionals.
Interface is not very user friendly	Very easy to learn interface.
Tableau server available for storing data.	Does not have storing data capabilities.
Used in medium and large scale organizations.	Used in all types of organizations.
MDX is used for measures and dimensions.	DAX is used for measures.
Embedding report is difficult for Tableau.	Embedding is easy in Power BI.

 

Power BI is used for creating dashboards related to Resource Management, Financial reporting, Sales scorecard, Claims, collection and billing, inventory optimization.

Some of the use cases of Tableau are as follows - 

IT — asset inventory, Service desk performance analysis, resource allocation

Finance — Budgeting, accounting, expense tracking

Marketing — Leads management, campaign management

Human Resources — Retention analysis, employee satisfaction.

Sales — Pipeline tracking

Facilities Operations — Workload distribution.

 

There are several data visualization tool available in the market like Tableau, Looker, IBM Cognos Analytics, Microsoft Power BI, etc. However, Tableau and Power BI is the most widely used Data Visualization tool.

 

Some of the basic differences are:

 

Parameter	Tableau	Power BI
Language	MDX	DAX
Platform	Mainly used for Data Visualization	Apart from data visualization, it can be also used for other data points
Volume	-          It can handle almost any volume of data -          It works better with the cloud data	-          Works better with only limited volume -          Performance dips if we use huge data from cloud
Usage	Most of the data analytics expert professionals can work on Tableau	Any professional with basic knowledge of tool can use this
Ease of using	Working on Tableau needs experience	Tool is very well designed for any new users to learn it faster
Speed & Performance	Is faster with multiple capabilities	Slower with ease of work
Cost	It needs both software and skilled professionals	This comes in bundle with Office 365

 

The targeted audience for both the software is completely different. As Power BI is coming bundled with Office 365 most of the organization prefer this. However, when we talk about analytics on huge data, it fails as the tool becomes very slow.

 

For me, due to ease of use and easy availability, Power Bi is better than tableau. As a Black Belt, we need to perform analysis extensively. In one of the recent examples, I had to club almost 83 excel files (of 83 professionals) with their few month of daily tracker. In no time, I was able to merge all these files into one sheet using Power Query (part of Power BI). Power Pivot (part of Power BI) helped in further slicing and dicing the data and get more insights. The data with the insight was then presented to the stakeholder with the Power BI.

Tableau which is now a group company of Salesforce Inc. – Started in 2003, Is an American company specializing in data visualization software development and services.

 

Power BI - It is originally developed by team working on SQL Server system and went on to become Power BI in 2013 as part of Microsoft windows / office 365 with foundation and additional features built on excel.

 

With around one decade more richer presence and pioneer in the data visualization services, Tableau scores very high among data visualization professionals and experts. For Amateurs and users looking for better ease and low-to-medium data complexity and visualization application, Power BI is normally initial choice. Tableau and Power BI can be compared in the below table.

 

 

Metric / Feature	Power BI	Tableau
Company	Microsoft Inc	Tableau Software Inc
Year of Inception	2011, formally named as Power BI in 2013	2003
Pricing position	Costs Less	Costs more
Data complexity, handling high data loads	4	5
Professional, expertise level	3	5
Usefulness for amateurs, students, basic needs	5	3
Integration with Microsoft Excel	High	Medium
Speed	4	5
Drawing action-oriented insights	4	5
Functionality	Limited data source connections	Can be connected to numerous data sources
Visualization	Moderate Visualization – visualization is basic but one can get 3rd party tool into Power BI	Advance Visualization – Capability to create advance visualization and there are blogs with complete step by step instructions available over internet to learn
Dashboarding	Open Dashboarding – It doesn’t have any fixed layout to create dashboard	Effective Dashboarding – More number for options available to create layouts and easy to enhance. Can find good examples in tableau public website
Data Modelling	Strong Data Modelling (Power Query) – Can bring in multiple tables and create data models to connect data	Lacks Data Modelling – One can’t produce high sophisticated data model in tableau but can create simple joins and unions.
Others	Strong Data Manipulation (DAX) – Using Data Analysis Expression one can create relatively complex dashboards	Strong Story Building – In a story one can bring 4-5 sheets or dashboards based on need ( to create)

 

Conclusion: Depending up on user and user needs either Tableau , Power BI or other competitive software can be used for Data Visualization

 

PS : Registered Trademarks of relevant companies are acknowledged. This article submitted in Forum is purely for academic purpose only. The comparison is based on limited understanding and insights from various resources available in public domain. No intended purpose to promote or favoring any product / service.

 

Data visualization is the art of presenting data with the help of graphical representation of information and data. It uses charts, graphs, and data visualization tools which helps the users with the details present in the data and provide essential insights. It is important in data science as it helps with the important insights and details which might get lost in the tables. 

The two prominent data visualization tools are Power BI and Tableau. Both are robust tools which helps the users with the data insights.

 

Here are the comparisons between the two – 
1.    Power BI is provided by Microsoft that can analyse, visualize, and extract insights from data. While Tableau is a powerful Business Intelligence tool that manages data flow and provides actionable information. 

2.    Power BI is easy to use, faster and performs better when the volume of data is limited while Tableau can cater to large volume of data.

 
3.    Power BI is a Microsoft product, it can easily be integrated with other Microsoft products.

4.    Power BI works on Azure Machine learning platforms along with SQL Server based Analysis Services while Tableau supports Python machine learning.

5.    Tableau is expensive as compared to Power BI
 

Business Intelligence(BI) technologies have been used extensively in the recent years for collection, integration, analysis and presentation of business information.

 

Power BI and Tableau are two such widely used technologies which performs data visualization to make sense of business data and insights.

 

Power BI

Power BI is more focused more on predictive modelling and reporting and was developed by Microsoft. The tool is capable of analyzing, visualizing and extracting  insights that can be shared across various departments in an organization. It was originally developed in 2010 by Ron George and was released to public in 2011.

 

Tableau

Tableau on the other hand was developed in 2003 at Mountain View, California and now stands acquired by salesforce. The two biggest advantages of Tableau is its low training cost and ability to handle huge volume of data as compared to power BI.

 

Tableau is suitable for medium and large organizations whereas power BI is suitable for small, medium and large type of organizations. It has data interpreter story telling ability however its biggest drawback is its inability to support AI and ML

 

Use Case:

Dash boards in companies and governments mostly fancies using Tableau as it is a more attractive and useful user interface as compared to Power BI.

Edited December 3, 20214 yr by C V Satish
spell check

Tableau:

Tableau is a data visualization tool used in business intelligence, to simplify the raw data to an user understandable format, involving visualizations in the form of dashboards.

 

Power BI:

Power Bi is also a data visualization tool used in business intelligence to convert data form various sources into interactive dashboards and reports .

 

Let us compare the advantage and disadvantages of each against the parameters listed below :

 

Power BI Vs Tableau

Comparison parameter	Power Bi	Tableau
Performance	Performs better with limited data and performance drops when bulk data is supplied.	Able to handle large volume of data quickly and doesn’t limit data points
User interface	Provides report view ,model view and data view in the user interface ,which very intuitive.	Provides cards and shelves, data source page, status bar, toolbar, sideband sheet tabs in the user interface and allows customizable dashboards according to the requirements.
User experience	Easy to understand and user friendly to operate	Customizable dashboards which encourages the user to experiment with data for desired results.
Ease of use	User interface connects with Microsoft applications provides an edge in ease of use.	Misses out on the easiness to interlink between Microsoft applications
Suability for organization	Suitable for small ,medium and large scale organizations	Suitable only for medium and large scale organizations
Data source support	Limited access to other data sources and servers compared to tableau.	Access to various data sources better than power BI in comparison
Supported data source examples	Microsoft Excel, Text/CSV, Folders, MS SQL Server, Access DB, Oracle Database, IBM DB2, MySQL database, PostgreSQL database, etc	Excel, Text File, PDF, JSON, statistical file, Amazon Redshift, Cloudera Hadoop, Google Analytics, drop box, google sheets, google drive and others.
Programming support	Supports Data analysis expression , M language , R programming	R Language ,- C, C++, Java, and Python.
Data Visualization	Attractive and visually appealing dashboards	Customizable dashboards, translating quires to visualizations.
Embedding of reports	Realtime embedding of report is easy	Realtime embedding of report is challenging
Machine learning	Enables the machine learning solutions using  Azure Machine learning, SQL Server based Analysis Services, data streaming in real-time,	Supports python machine learning
Products available	Power BI Desktop	Tableau Desktop
	Power BI Service	Tableau Desktop Personal
	Power BI Data Gateway	Tableau Desktop Professional
	Power BI Report Server	Tableau Public
	Power BI Mobile Apps	Tableau Server
		Tableau Online
		Tableau Reader
Customer support	Smaller community to support, considering the application is relatively new.	Extensive user base and high online user community groups to support.

Data visualization contains graphical representation of the data. This is most usual way of addressing the progress or performance of a process or a unit or a whole CoE. They are presented in the form of Time-series, Ranking, Part to whole, Deviation, Frequency distribution, Correlation, Nominal Comparison, Geographic/Geospatial.

Power BI & Tableau are the 2 most used tools for data visualization.

Power BI is Microsoft Product, and the Tableau was an independent provider, later acquired by the Salesforce (2019).

Feature	Tableau	Power BI
Volume	High data processing capacity with high performance	Limited data processing
Good for	Whole Visualization	Data Points Visuals
Support	Excellent Customer Service Support	Customer Support provided to paid Users and the response delayed for free users
Learning	Requires some understanding and time consuming in learning the Tableau because of its vastness	Very easy to learn. Mostly drag & drops functions
Reporting	Embedded reporting is tough	Embedded reporting is easier compared to Tableau
Cost	High	Low compared to Tableau
AI Integration	Difficult or not possible to integrate AI, though there is provisioning of Python & R Programming	Completely Provisioned to integrate with Python & R programming to breed AI models
Data Size	Unlimited data file Size Acceptance & Processing	Data file acceptance can be 1 GB (max). Power BI cannot process beyond it.
Storage	Server Storage	Designed for reporting and analytical visuals, no storage provisioned

 

Both Tableau and Power BI are great applications for creating Dashboards and visualizing data.

It is difficult to recommend one over the other as both the tools have unique features to offer.

 

Selecting the right applications totally depends on specific needs of the workgroup.

Such as, if the intension is Visualization (Visual Analytics), Tableau would be great pick and If the group is more interested in Predictive modelling and Reporting, Power BI offers great capabilities.

 

Both tools are integrated with R & Python languages.

 

As per 2021 Gartner Peer Insights (based on ~5881 individual reviews from Analytics and Business Intelligence market space),

 

Tableau takes upper hand on the below capabilities:

• Interactive Visual Exploration
• Analytics Dashboards
• Publishing Analytic Content
• Embedding Analytic Content
• Quality of End-User Training
• Timeliness of Vendor Response

Power BI edges over tableau in:

• Collaboration & Social BI
• Mobile Exploration and Authoring
• Self-Contained Extraction, Transformation & Loading (ETL) & Data Storage
• Self-Service Data Preparation
• Governance and Metadata Management
• Security and Use Administration
• Cloud BI
• Pricing Flexibility
• Ease of Deployment
• Ease of Integration using Standard APIs and Tools

 

In my opinion, I have seen POWER BI to be comparatively easier, especially for new users who are not data analysts. Data scientist prefer Tableau over power BI, due to its advanced functionality in creating visuals 

The two leaders in the BI market according to the Gartner 2021 report are Power BI and Tableau. Tableau has been around since 2003 and Power BI was launched in 2011 and added to the Office 365 suite in 2013.

Power BI

Power BI is a Business Intelligence software, that was added to the Microsoft family as a SaaS model. It is very closely related to Excel. It consists of a group of applications and services that are on the cloud. The main apps amongst others are Power Query, View, Pivot, Map, and Q&A. With its integration with Excel, it is very easy to create dashboards and reports, hence, it is the go-to tool for inexperienced BI users. Microsoft has added Power BI to its Power Platform which includes the Power Virtual Agents, Power Automate, Power Apps, etc.

Its disadvantages are that it offers less functionality than Tableau. Also, in order to get its full functionality, you need to install the SQL server and the Report Service.

Tableau

Tableau was introduced as a BI software in 2003. It is more powerful than Power BI. It is one of the go-to software for Data Visualization.  Tableau has a strong user community and has an end-to-end solution that begins from collaboration, moves on to analytics, the discovery of content, preparation of data, access of data, and deployment. Tableau is more flexible than Power BI. The desktop version of Tableau can be installed without the installation of the SQL Server.

Its disadvantages are that it is much more expensive than Power BI and its learning curve is steeper than Power BI since it needs you to build your own data warehouse. Further, the Tableau licenses have incremental costs, and connecting to third-party service providers adds to the cost.

Similarities between Power BI and Tableau.

Both Power BI and Tableau can create a variety of Data Visualizations such as bar, line, pie charts, tree, geographical maps. The visualizations are interactive on both the software with them having features such as filtering, creating dashboards, etc. Both the software can be connected to various data sources, are user-friendly and require no coding.

Differences between Power BI and Tableau

Power BI works only with MS-Windows and can be easily integrated with Microsoft, however since Tableau has been acquired by Salesforce, its integration with Salesforce is easy.

R and Data Visualization

R is free software that was initially used for statistics and graphics. The R Core team and R Foundation for Statistical computing support its development. It has been under development since the early 1990s and is available under the GNU General Public License. It is available for various operating systems. Besides the command line interface, it can also be integrated with third-party GUI such as RStudio and various IDE such as Jupyter.

Since R is open source, it is extensible through functions, and packages. The R community is constantly contributing and improving its functionalities. Besides great libraries for Data Visualization, it has numerous libraries for statistics, linear and non-linear modelling, spatial, time series, machine learning, and artificial packages for classification, clustering, computer vision, etc.

Comparing R to Power BI and Tableau.

As an open source, R is free, it is being developed by a vast community of R Programmers and has the latest packages in most of the domains. Even though the learning curve is steep, its data visualization package is comparable to both Power BI and Tableau. Besides this it has great packages for Simulation, Machine Learning, Artificial Intelligence, etc.

References

https://spreadsheeto.com/power-bi-vs-tableau/

https://www.datacamp.com/community/blog/power-bi-vs-tableau

https://en.wikipedia.org/wiki/R_(programming_language)

In today’s world it is very important to understand the data for actionable insights. Data visualization is of utmost importance which helps us to understand the patterns, insights and multiple layers of the data. It not only simplifies the understanding of the data but also helps in getting nice visualisations which are eye catchy.
 
Data visualization charts like bar charts, scatterplots, line charts, waterfalls, funnels, geographical maps, etc. are extremely important. They let us understand the information by looking at them. Normally we would have to read spreadsheets or reports to understand the data. Data Visualization allows analysts to create effective visual data models according to their needs and specifications conveniently.

 

Few of the tools are as below:
1. Tableau
It is a data visualization tool used by data analysts, data scientists etc. to visualize the data and get insights based on it. 

 

2. SAP Analytics Cloud
It uses business intelligence and data analytics capabilities that evaluates your data and create visualizations predicting outcomes. It provides tools that helps to identify possible errors in the data and categorizing different data measures and dimensions.

 

3. Microsoft Power BI
It is a data visualization platform that focusses primarily on creating a data-driven intelligence. It offers self-service analytics tools which can be used to analyse and share the data.

 

4. Looker
Looker tool that can go in-depth in the data and analyze it to obtain useful insights. Looker provides real-time data dashboards for more in-depth analysis enabling instant decisions.
 
5. Zoho Analytics
It is a Business Intelligence and Data Analytics software that helps create data visualizations. It can obtain data from multiple sources and mesh it together to create multidimensional data visualizations.

 

6. Sisense
It is a business intelligence-based data visualization system and provides various tools that allow data analysts to simplify complex data and obtain insights.

 

7. IBM Cognos Analytics
It is an AI based business intelligence platform supporting data analytics along with visualisation.

 

8. Qlik Sense
It helps companies to become data-driven enterprises by providing an associative data analytics engine, sophisticated Artificial Intelligence system, and scalable multi-cloud architecture allowing to deploy any combination of SaaS, on-premises or a private cloud. 

 

9. Domo
It is a business intelligence model that contains multiple data visualization tools providing a consolidated platform where data analysis can be performed thus creating interactive data visualizations enabling users to easily understand your data conclusions. 

The winning answer was provided by Prashant Philip Vargis for providing the use cases for both Tableau and Power BI.