Blog_Banner_Asset
    Homebreadcumb forward arrow iconBlogbreadcumb forward arrow iconData Sciencebreadcumb forward arrow iconTableau V/S Power BI: The data visualization Leaders vie for data analysts’ attention

Tableau V/S Power BI: The data visualization Leaders vie for data analysts’ attention

Last updated:
31st May, 2023
Views
Read Time
9 Mins
share image icon
In this article
Chevron in toc
View All
Tableau V/S Power BI:  The data visualization Leaders vie for data analysts’ attention

We are visual creatures. We see colors, patterns, and shapes to make sense of the world that we live in. In an age where data is overflowing from all corners of the world, it helps to simplify it into images that we can easily consume.

This is where data visualization steps in, and it is more than just bar graphs or pie charts. It’s almost an art of putting form to functionality. 

Why is it necessary?

Data visualization allows one to take the data back to a point where convoluted problems can be made easy and interesting to solve. One can arrive at a solution only when complex data is made understandable. There are numerous large databases for one single product, but how does one decide on an actionable point?

In that complex data, there is a story waiting to be discovered and told. To present that story, one requires a knack of presenting it in an interesting way while balancing factual data points and weaving a well put together scenario that enables business. 

What are the challenges?

Despite data visualization being the most effective way of understanding data, it comes with its drawbacks. Here are some of the most pressing ones.

  • Differences in the level of understanding

Even in organizations spread worldwide, data is still represented in the form of bar graphs and is rarely interactive. It may be necessary for more complex visualization to increase data literacy, reduce waste of resources, and benefit business effectively.

  • A dearth of skilled personnel

A shortage of data scientists and skilled resources who can feed the right data to the right people continues to be a big challenge. At present, most data visualization experts are freelancers, and dedicated teams have only just begun to crop up in organizations.

  • Data is collected without a plan or with a bias

Establishments spend an inordinate amount of their time and resources in cleaning and processing data instead of visualizing it. The other concern is that any bias in data becomes a hurdle in making correct visualizations for decent predictions.

What are the tools that help in troubleshooting them?

Although there is various data visualization software available in the market, Tableau and Microsoft Power BI appear on the leaderboard as popular tools preferred by data visualization practitioners. Tableau, established almost a decade before Power BI, remains one of the most used platforms. However, Power BI has successfully played catch up in the last three years and made a place for itself replacing Qlik.

Tableau and Power BI: Which offers better usability?

Source

With Tableau and Power BI being the top tools used for data visualization for a while, let’s take a look at which software offers the most optimum ease of working and suits best to the practitioner’s abilities based on the following parameters.

1. Cost

Power BI, a service made and provided by Microsoft, has a simple pricing model that reflects the same approach employed in Microsoft Office 365. On the other hand, Tableau assumes a deeper usage level at $500 per user/per year with virtually no limit on data. Tableau also goes well beyond a simple per-user subscription model to provide a wide range of licensing options based on the specific roles individuals play within an organization. 

Source

2. Easy to use

Power BI has a slight edge over Tableau in terms of its user interface that has roots in Microsoft Office 365, which most end-users are already familiar with and do not need to make additional payments for as it’s a part of the Microsoft stack offering. That also means, no additional licensing (only for advanced users) is required. 

However, Tableau is an independent platform and enjoys a certain popularity among novice users as it is quite easy to navigate. When it comes to drilling down into data, Tableau provides some notable advantages. It is investing in natural language capabilities specifically designed for BI use cases; it facilitates deep exploration with advanced analytics and provides a community environment where easy accessibility is paramount. Also, the turnaround time for Tableau is rather swift in comparison, Power BI may take almost the same time as the task. 

Source

Explore our Popular Data Science Degrees

3. Market share

A total of 25,109 companies are using Microsoft Power BI, which is almost half compared to Tableau, which boasts of 49, 366 customers. Also, last year, Salesforce, a cloud-based software company, expanded by acquiring Tableau for $15.7 billion. Tableau Software Inc. has achieved revenue growth of 14.1 % and improved market share to approximately 12.19 %.

Source

Our learners also read: Top Python Courses for Free

Read our popular Data Science Articles

upGrad’s Exclusive Data Science Webinar for you –

Watch our Webinar on The Future of Consumer Data in an Open Data Economy

Top Essential Data Science Skills to Learn

Pros and Cons of Power BI and Tableau

As some of the most popular software for data visualization, users need to analyze the advantages and disadvantages of both software to explore the difference between Power BI and Tableau

  • Advantages of Power BI

Microsoft Integration: Since Microsoft has developed Power BI, the tool is compatible and integrated with Excel, SharePoint, SQL Server, Azure and other Microsoft products for smooth functioning. 

Usability: PowerBI offers an intuitive learning curve for new users and is easy to navigate for those familiar with Microsoft 365. It allows for the quick creation of dashboards and reports, even by those who might not have technical expertise.

Affordability: When it comes to Tableau vs Power BI, Power BI offers a free version as well as a low-cost plan. Businesses can get different subscription plans according to their size and needs. Power BI offers an entire range of features at a much lower price. 

  • Disadvantages of Power BI

User Interface: The interface is much more cluttered with bars and icons that often block the view of crucial information, reports and dashboards.

Limited data connectivity: Power BI has a tough time handling relationships between complex tables. The process is time-consuming, and one might have to create new fields only to join tables.

Restriction of features: There are several limitations while using the free version, including limited data capacity and limited features.

  • Advantages of Tableau

High Performance: Tableau offers users advanced data visualization and data transformation abilities. Moreover, it has a faster data processing power for large data sets. 

Customization: The tool also provides various visualization tools such as graphs, charts, and more for easier analysis of data and more customization features.

Increased Data Connectivity: The tool provides flexibility when choosing data sources and allows multiple connections to various data sources for informative reports.

Community support: Users can approach the active Tableau community for tips, resources and help with a promise of finding a solution to most problems.

  • Disadvantages of Tableau

Expensive: It can be expensive to implement Tableau, especially for smaller companies where the decisions are taken with an eye on the finances. When it is about choosing between Power BI or Tableau, the cost is a major concern.

Steep learning curve: Beginners need to have proper training in programming languages and data analysis to effectively use Tableau. It is also more challenging to grasp than Power BI. 

Microsoft Integration: Tableau uses a single sign-on process to integrate with Microsoft products like Office 365, Dynamics 365, and Microsoft Flow.

Correct data visualization and the impact on business

Data visualization is a great way for companies to communicate information, both internally and externally. It’s a tool for businesses to become storytellers. To navigate raw data, it is imperative to find the needle in the haystack. Also, charts and maps can help businesses efficiently evaluate their employees’ sentiments and take appropriate action to create a more enjoyable work experience.

Visualization tools automate the process of organizing information, which helps businesses make faster decisions. For most companies, sales and marketing departments rely on the fast turn around of data visualization tools. A well-defined business case is capable of giving you, as a data visualization practitioner, the necessary insights into what your client’s needs are. 

Learn data science courses from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career.

Here are a few examples of my own work that you can study for reference.

WFH Readiness: How prepared are we as a planet?

Women in power: Global representation of women in politics from 1997-2019

Do you want to reduce the carbon footprint? Focus on what you eat, not whether your food is local.

Sources:

Technology Advice | Experfy.com | The Innovation Enterprise | Tableau.com | Medium.com |  It Business Edge | Encorebusiness.com | Pubs Online | SelectHub | Technology Advice | Medium.com | Data Flair Training | Data Chant | Appsruntheworld.com | 360suite.io Appsruntheworld.com | Medium.com | CSI Market

Profile

Siddharth Pawar

Blog Author
With experience in the field of Information Technology and a wide range of work published on Tableau, Power BI, MicroStrategy, and Google Studio, he is proficient in creating data visualizations, complex dashboards using BI tools. He currently works as a Senior Consultant at Fractal Analytics.

Frequently Asked Questions (FAQs)

1Which one is better – Power BI or Tableau?

Tableau is a widely used data visualization tool that allows businesses to simplify the raw data and present it in a readable format. It has the capability to handle a huge volume of data without hampering the performance. The users get a chance to utilize 24 different types of visualizations.
On the other hand, Power BI is useful for converting your raw data from different sources into an interactive dashboard and also generating Power BI reports. Power BI has the capability of handling only a limited volume of data. This one is considered to be a suitable one for all types of organizations.
Both Power BI and Tableau are known to be the best ones when it comes to data visualization tools. Choosing any one would completely depend on your use. The only thing that you need to keep in mind is that Power BI can only handle a limited volume of data, while Tableau has the ability to manage a huge volume of data effectively. On the other hand, Power BI is easy to learn, but you will have to put in more effort to learn Tableau.

2Is Power BI good for data visualization?

Power BI is a data visualization tool provided by Microsoft that helps the users to analyze the data by providing it in a visual format. Power BI is a very powerful tool for analyzing data from different sources and formats. The drag-and-drop interface makes it pretty easy for the users to learn and start using the tool. This feature allows the users to sort, compare, and analyze the data very quickly. Power BI is definitely an excellent one for data visualization.

3What are some of the best alternatives to Microsoft Power BI for data visualization?

When it comes to data visualization, you need to get the best tools for making the entire process smooth and easy. With the right tools, you will be able to curate actionable insights from the raw data available. Here are some of the best alternatives to Microsoft Power BI:
1. Tableau Desktop
2. Qlik Sense
3. Domo
4. Sisense
5. Oracle Analytics Cloud
6. Looker
7. ThoughtSpot
Tableau is the next tool one would consider after Microsoft Power BI as both are known to be the best ones in the data visualization industry.

Explore Free Courses

Suggested Blogs

Top 13 Highest Paying Data Science Jobs in India [A Complete Report]
905217
In this article, you will learn about Top 13 Highest Paying Data Science Jobs in India. Take a glimpse below. Data Analyst Data Scientist Machine
Read More

by Rohit Sharma

12 Apr 2024

Most Common PySpark Interview Questions & Answers [For Freshers & Experienced]
20906
Attending a PySpark interview and wondering what are all the questions and discussions you will go through? Before attending a PySpark interview, it’s
Read More

by Rohit Sharma

05 Mar 2024

Data Science for Beginners: A Comprehensive Guide
5067
Data science is an important part of many industries today. Having worked as a data scientist for several years, I have witnessed the massive amounts
Read More

by Harish K

28 Feb 2024

6 Best Data Science Institutes in 2024 (Detailed Guide)
5171
Data science training is one of the most hyped skills in today’s world. Based on my experience as a data scientist, it’s evident that we are in
Read More

by Harish K

28 Feb 2024

Data Science Course Fees: The Roadmap to Your Analytics Career
5075
A data science course syllabus covers several basic and advanced concepts of statistics, data analytics, machine learning, and programming languages.
Read More

by Harish K

28 Feb 2024

Inheritance in Python | Python Inheritance [With Example]
17631
Python is one of the most popular programming languages. Despite a transition full of ups and downs from the Python 2 version to Python 3, the Object-
Read More

by Rohan Vats

27 Feb 2024

Data Mining Architecture: Components, Types & Techniques
10801
Introduction Data mining is the process in which information that was previously unknown, which could be potentially very useful, is extracted from a
Read More

by Rohit Sharma

27 Feb 2024

6 Phases of Data Analytics Lifecycle Every Data Analyst Should Know About
80741
What is a Data Analytics Lifecycle? Data is crucial in today’s digital world. As it gets created, consumed, tested, processed, and reused, data goes
Read More

by Rohit Sharma

19 Feb 2024

Sorting in Data Structure: Categories & Types [With Examples]
139098
The arrangement of data in a preferred order is called sorting in the data structure. By sorting data, it is easier to search through it quickly and e
Read More

by Rohit Sharma

19 Feb 2024

Schedule 1:1 free counsellingTalk to Career Expert
icon
footer sticky close icon