Data Visualization

Data Visualization Tools

Data visualization may appear to be a complicated term, but to put it simply: It is a graphical representation of data. As a Data Scientist, data visualization has become a part of my job, and I use data visualization tools very often. I’ve come across many data visualization tools and realized the power of visualization over the years.

We as humans tend to visualise everything in terms of colours, patterns, and textures. This aids us in remembering and forecasting future events. Similarly, these data visualization tools assist us in creating easily understandable visual representations, making it easier to understand and simplify complex data sets.

Data visualization tools enable you to combine data from various sources, shape it, and present it in a way that helps you understand what’s happening in the business world. This will help you identify threats coming your way, and you’ll also be able to spot opportunities that will help you grow your business.

In this article, I’ll go over the most popular visualization tools and their features, as well as introduce you to some of my favourite tools that I use frequently and occasionally for visual storytelling.

1. Tableau Public

Tableau Public

Tableau is one of my favorite tools, I like the features that it offers and also it’s a free tool, you can get the public software of Tableau for free and you can use it and learn it for free. Tableau is an in-demand skill and with just Tableau you are open to a wide array of job opportunities like Data Analyst, Business Intelligence Analyst, Data Scientist, etc. The one more thing that I like about Tableau is that it’s very simple and easy to use, you do not have to be a techie or a Coding expert to work on Tableau. It is one of the best tools for beginners. 

Tableau is a popular analytics platform that not only allows you to create appealing graphics but also to work with a variety of analytical methods and techniques, such as aggregation, parameters, trend analysis, forecasting, clustering, statistical analysis, etc. Tableau is a must for anyone who works with data.

2. Power BI

Power BI

Power BI is a Microsoft Business Intelligence application. Power BI has evolved over the years and I can assure you that it will be one of the leading visualization tools on the market in 2024. When it comes to the features of Power BI, the first feature I like the most is report sharing. With Power BI you have multiple options, you can view the reports in the browser and on mobile and you can also embed Power BI reports live in a PowerPoint presentation, which is not possible with some visualization tools. 

Power BI is easy to use and implement. If you can use Excel, you can use Power BI. To get started, you can download the Power BI desktop app from the Office store and use it for free. You don’t need to be an IT expert or have Programming skills to work with Power BI. Power BI can do so much more, it goes beyond creating fancy reports. You can create detailed reports with advanced analytics, time intelligence, drill-down and drill-through, what-if analysis, etc. To summarise, Power BI is the future and learning this tool will help you get ahead of your career.

3. Data Wrapper

Data Wrapper

Data Wrapper was developed by a team of 20 people from the company Datawrapper GmbH. When it comes to the features of Data Wrapper, you can primarily do three things, first, you can create charts that you can imagine, such as doughnuts, bars, line charts, etc. and then you can create a map. That’s one thing that I think is much better than Power BI because there are problems with creating district-wise data or anything tricky, whereas in Data Wrapper we find a comprehensive list of maps that we can work on. The third point is that you can create a table with different analyses. These are the three things that a data wrapper can do. However, the disadvantage of the data wrapper is that we cannot create extensive data set visuals or elaborate stories.

4. Infogram

Infogram

Infogram is a simple visualization tool that helps you to create beautiful content, if you have good data and don’t know how to present it, you can try Infogram visualization tool. It helps you to create smart visualizations with good designs, images, and infographics. This helps people to understand the content easily and effectively. 

The Infogram tool helps you to create social media visuals, infographics, reports, slides, dashboards, and maps. If you are a Blogger, Graphic Designer, Journalist, or visualizer, then Infogram is the best visualization tool for you. 

5. Google Data Studio

Google Data Studio

Google Data Studio which is now popularly known as Looker Studio, is an easy-to-use visualization tool that allows you to implement your project in a matter of days as a beginner. It is a free tool on several levels, but to use advanced features, you must upgrade to the premium level. However, it functions the same as any other Google product.

Google Data Studio may not be the best solution for larger businesses due to its limited features. Another disadvantage of Google Data Studio is that it does not work well with data that is not synchornized with Google and does not automatically handle miscalculated values. As a result, I believe Google Data Studio’s visualization tool is best suited to small businesses.

  • Plotly

Plotly

Plotly is one of the great data visualization tools to have if you’re working on building any type of analytical presentation or trying to interpret results. Plotly is an incredibly powerful library with Python for Data Science, Machine Learning and Artificial Intelligence related operations. You can use Plotly online, offline, and in Jupyter Notebooks which allows you to build extremely powerful and interactive visualizations with data. 

To use Plotly, you must have a little coding experience or a coding background. Plotly is best for developing interactive visualizations, it runs mainly on the browser and a few lines of code are all you need to make wonderfully looking charts and it is a very convenient platform for using large data sets.

  • Matplotlib

Matplotlib

Matplotlib provides a wide range of tools for creating high-quality visualizations in Python. It supports a variety of plot types, including line plots, scatter plots, bar plots, histograms, and many more. Matplotlib also provides a range of customization options, including the ability to adjust colours, labels, fonts, and other visual elements. 

Matplotlib is more professional and more scientific because of its countless customization options, to create some very good-looking Matplotlib charts you need to take some time, often you need to write your little mini framework to get it to work. With Matplotlib you can do everything you want but you have to customize it in a little bit more complex ways. Matplotlib has a variety of options and customizations available. It’s more professional and used for scientific papers and you should know how to use it if you are a Python Developer or Data Scientist. 

  • QlikView

QlikView

QlikView is Qlik’s original data analytics app. It is built for guided analytics and offers good flexibility in data analysis. I use Qlikview to access different reports, dashboards, and calculations. With Qlikview, users with no knowledge of data analysis are not able to make their visualizations. For developers and non-developers alike Qlikview is made to be collaborative, you can use this software from your computer, tablet, or phone. Its communication tools like instant messaging and commenting make it easy to ask questions to colleagues. 

Qlikview is better for in-house developers or data scientists, if you work with very large complicated datasets or if you want to specifically focus analysis on certain reports and metrics.

Final Thoughts

In today’s fast-paced world, we have an information overload problem, and the solution is to use data visualization. Visualizing information and designing it to make more sense or tell a story allows us to focus only on the important information.

Data visualization tools therefore play an important role in visualizing and understanding interesting data. These tools can help data scientists, analysts and anyone else who works with data. All tools have their pros and cons, but looking only at the data visualization aspects, I can say that Tableau is the winner here, because data visualization in Tableau is a core concept and the best tool for data scientists and big data analysts. I hope this article has helped you to find the best visualization tool for your needs.

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