Free Resources for Data Visualization

Looking at data and trying to gain value from it can be daunting, especially when you have thousands or millions of records to peruse or analyze. Regardless of the size of your dataset, it’s very important to examine data in a manner that’s easy to digest. In other words, it is often easier to understand data if it’s in a visual format. Putting data into a visual format is called Data Visualization. This is essentially the process of creating charts, graphs, matrices, word clouds, tables and more to get an overall understanding of the trends in the data. There is a specific process called Exploratory Data Analysis (EDA), where data analysts/scientists visualize the data so that they can start seeing important patterns that they may need to investigate further. In this case, data visualization is used to do some level of preliminary analysis such as finding the most popular brand in a dataset (bar chart) or seeing whether sales increased or decreased over time (line graph). This is basic information that we can gain from looking at the data in a visual format as opposed to tabular or comma separated formats. In other cases, data can come from multiple sources, so visualizations are created as a means of putting the data together with the goal of telling a single story. Data visualization is very useful if your goal is to learn something or retain information. As a data scientist/analyst, your goal is always to learn what the data is saying, so data visualization can be a vital tool in the EDA process and beyond. My favorite thing about data visualization is the ability to group data points and compare them or see how they are correlated or how one thing may be affecting something else. To me, data visualization, especially in the EDA stage, helps me to determine what I’m going to investigate and how I’m going to investigate it. In the following sections, I will expound on some FREE data visualization tools that you can use to analyze data. Most of these resources accept data in various formats such as CSV, JSON, XLSX and more, so usually a matter of preference or your project goals will determine the software you decide to use.

Tableau Public

If you’ve heard of Tableau, you’ve probably heard about the desktop version which you have to pay for. However, there is a free version of Tableau called Tableau Public, which allows you to do the same things for free. For the most part, Tableau Public allows you to upload data and create typical visualizations. As the name suggests, it is a public space, so you would be able to find visualizations that others have created and you may have to agree to share the data that you used for your visualizations. Thus, Tableau Public may not be suitable for you if you are working with sensitive data that you don’t want others to have access to. If you are just practising or working on publicly accessible data, I would recommend using Tableau Public. It’s very user friendly and the drag and drop options make it easy to visualize data, especially if you’re not proficient in coding.

Power BI Desktop

If you love Microsoft Products, this one is for you! Power BI Desktop is a free desktop software created by Microsoft for users to visualize data. If you already use the Microsoft Office Suite or other Microsoft products, integration is typically simple. For example, if your data is in an Excel spreadsheet, you can import it into Power BI or if you are creating a PowerPoint presentation, you can integrate your charts from Power BI into your slides. There are other data formats that can be imported into Power BI such as CSVs, so you may still be able to use it even if you’re not using other Microsoft products. Power BI works great if you’re using a Windows machine but if you are a Mac user, this option is not for you unless you have a virtual machine with a Windows Operating System installed on your device. Overall, if you are looking for something you can install locally where you don’t have to share your data or visualizations with the world, Power BI Desktop will do the job. You also don’t need to integrate it with other software if you wanted to do a presentation based on your findings. You could simply take screenshots and add them to the presentation slides.

Google Data Studio

Another free visualization tool is Google Data Studio. One of the perks of using this is that you don’t have to download anything to work with this platform. Everything is online. Users can connect to data sources in the cloud or upload static files to create visualizations and dashboards. One of the features that I find very interesting is the ability to connect to external webpages. For example, you can create your own charts on some pages, but if there is something interesting that you found on a website, instead of recreating it, Google Data Studio allows you to link your page to that external website and display the content in your Google Data Studio file. This platform enables users to create different types of charts, but may not be very user friendly for first timers. However, there are many internet resources to help you navigate and accomplish your goals with Google Data Studio. One downside is that there are some access limitations depending on which country you’re in. Otherwise, it’s a great free resource to use for creating dashboards.

Google Sheets

Many people are already familiar with Google Sheets as an online spreadsheet editor, but it can also be used for creating visualizations. Data can be “sliced and diced” and various charts can be created. If you are working with big data, one limitation is that Google Sheets only holds up to 10 million cells, so this may not be a good place to keep the data as there will be a cutoff point. However, if your data takes up less than 10 million cells, you should be fine.

Python & R

For more technical users, the Python and R programming languages are free resources that you can use to create visualizations. Although they are used for much more than just visualizations, they are excellent tools where you don’t necessarily have to worry too much about the size of your data. Since these are programming languages, they will require you to install some things on your machine including a good text editor. However, I also like to use Google Colaboratory when coding in Python because this is an online platform that enables you to write code, create visuals, add paragraphs and essentially personalize the data storytelling experience. Google Colab is not a visualization platform, but it’s a coding platform that you can use to create charts as you explore data.

I love finding opensource/free resources that help with my data science journey. They provide an opportunity for me to sharpen my skills in my spare time without having to spend anything at all. It’s unlikely that large organizations would use free software, but more often than not, the skills you learn while using the free versions of these platforms are transferrable. So, if you learned how to do something in Tableau Public, it’s likely that you can do the exact same thing in Tableau Desktop, and so on. If there are other visualization tools that are not on this list, feel free to leave a comment and add to the list!