Big Data Visualization Tools: Types, Benefits, and How to Choose

Key takeaways

Big data visualization tools translate large volumes of complex data into manageable, easy-to-understand information.

• Data visualization can help you generate ideas, make informed decisions, and educate your colleagues and stakeholders.

• Data visualization tools include stand-alone software such as Tableau, cloud-based platforms such as Amazon QuickSight, and open-source libraries such as Plotly.

• You can choose data visualization tools based on cost, scalability, your needs, and your technical skills.

Discover types of big data visualization tools and the software and platforms you can use to transform your data from complex and numerous to accessible and easier to understand. If you’re ready to advance your data skills, consider enrolling in the Google Data Analytics Professional Certificate. In as little as six months, you’ll have the opportunity to learn how to clean, organize, and visualize data. Upon completion, you’ll have earned a shareable career credential.

Understanding big data visualization

Big data refers to the vast amount of data businesses and organizations collect. Without the help of big data tools, the volume and variety of this data make it difficult to store and analyze.

These tools include big data visualization tools, which take the data once it's analyzed, or even in raw form, and turn it into something you can view and read. Seeing data visually allows you to discover patterns and inconsistencies and communicate findings simply and clearly.

Benefits of data visualization

In addition to simplifying the data in a way that allows you and others to understand it better, data visualization brings several benefits to your organization:

• Generating ideas: Viewing data visually gives you a starting point for brainstorming and generating ideas within your teams and organizations.

• Making decisions: Data visualization gives you the means to make data-driven decisions and solve problems within your business.

• Teaching and training: Visual data allows you to explain and highlight concepts and patterns in an accessible way, making it a valuable tool for educating your staff and stakeholders.

Read more: What Is Data Visualization? Definition, Tools, and Examples

Types of big data visualization tools

You'll find different tools helpful in exploring different data sets and for different objectives. While there are numerous ways to display your data, not every visualization option suits all types. For example, if your data represents a time series, a line graph is an excellent way to display it. However, a heat map wouldn't work for this, as heat maps are most effective for geospatial information (data on location). 

Choosing the right visualization tools for your data is crucial; otherwise, it can complicate your data. Various data visualization tools are available on the market, including stand-alone software, cloud-based platforms, and open-source libraries.

1. Stand-alone software

Stand-alone data visualization software comes in many forms, many of which are beneficial for enterprises, small businesses, and individuals who work with data. It is a low-cost alternative to cloud-based platforms and is accessible even to beginners and non-technical users. 

Stand-alone data visualization software generally has an interactive dashboard that allows you to track data and create a range of visualizations. These include charts, maps, graphs, infographics, and geospatial arrangements, to name a few. Examples of stand-alone data visualization tools include:

• Tableau: One of the most widely used and well-known data visualization tools, Tableau also offers a free version that lets you store visualizations publicly. This software is accessible to those without technical expertise and gives hundreds of visualization options.

• Microsoft Power BI: Another popular data visualization tool, Microsoft Power BI offers a range of data visualization options at a low price. This tool is a little more complicated to use if you don't have a technical background. 

• Infogram: With its drag-and-drop functions, Infogram is excellent for beginners. In addition to a range of visualizations, it's highly effective in creating infographics. 

2. Cloud-based platforms

Cloud-based big data platforms enhance data storage, analysis, and visualization by increasing the storage available and providing quick and easy access to data. A cloud-based platform also offers increased security and automated backup, reducing the risk of losing data.

Cloud-based big data visualization platforms to support your business functions include:

• Looker Studio: This platform offers a catalog of data visualization options, including templates to simplify the process.

• Amazon Quick Sight: This generative BI platform allows you to use visualizations to work with data summaries and interactive stories to improve decision-making. You'll find various digital display options, including simple bar charts, radar charts, and waterfall charts.

• Microsoft Azure Data Explorer: This cloud-based tool integrates with multiple visualization tools and plug-ins, including Power BI, Excel, Grafana, and Kibana, offering a wide range of visualization options. 

3. Open-source libraries for data visualization

Another option for your big data visualization needs is using an open-source library. If something is open source, it means it is free for anyone to use, modify, and redistribute. Developers use open-source libraries to build custom visualizations and integrate them with free data visualization tools.

Examples of open-source data visualization libraries where you can find custom visualizations and plug-ins include:

• D3.js: An open-source front-end JavaScript library for data visualizations using HTML, CSS, and SVG, D3 has a community of award-winning designers worldwide. It's regarded as the foundation for similar higher-level chart libraries.

• Apache Echarts: This lightweight canvas library uses JavaScript and ZRender to offer highly customizable, interactive charts that can be added to presentations and products.

• Plotly: Plotly is an interactive open-source library for charting. It supports over 30 types of charts using Dash for your data visualizations.

Can ChatGPT do data visualization?

Yes, ChatGPT can create data visualizations. By providing ChatGPT with data, the large language model can help you identify what data to visualize and what types of visualizations to create. You can also use ChatGPT to create different types of visualizations, such as line plots, bar charts, graphs, and more.

Key considerations in choosing the best visualization tools for big data

You'll find a range of different options for data visualization tools. What you choose depends on several factors, including:

• Cost

• Your technical abilities

• Scalability

• How it fits your purposes

The tool you select must be relevant to the data you want to display. Selecting a tool that isn't right for your data can skew your presentation and misrepresent your data.

It is also important to note that your data visualizations rely on accurate, meaningful data, so you must make sure your data sources and data analysis foundations are solid.

Discover free data analysis resources

Join Career Chat on LinkedIn, where you can stay up-to-date on career tips and industry trends. Then, explore these resources to learn more about data analysis and visualization:

• Watch on YouTube: What Is Data Wrangling? The Key to Clean Data 

• Learn your terminology: Data Analysis Terms and Definitions 

• Read an insider story: Meet the Data Analyst Using His Creativity to Tell Visual Stories 

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