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

Big data visualization tools effectively translate large volumes of complex data into manageable and easy-to-understand information. This information is useful for making business decisions, creating visual reports, and presenting details to stakeholders, clients, and staff. 

Visualization tools allow you to view data to see patterns and trends. This might be a simple representation, such as a graph, table, or chart, or something more in-depth, such as a treemap, pie chart, or histogram.

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. 

Understanding big data visualization

Big data is the name of 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 in a visual format allows you to discover patterns and inconsistencies, and to communicate findings simply and clearly. 

Benefits of data visualization

As well as 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.

Types of Big Data Visualization Tools

You'll find different tools useful for 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 make your data more complicated. You'll find various data visualization tools 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 for those without technical expertise and offers hundreds of visualization options.

• Microsoft Power BI: Another popular data visualization tool, Microsoft Power BI offers a range of data visualization options and 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 amp up data storage, analysis, and visualization by increasing the storage available and giving quick and easy access to data. A cloud-based platform offers increased security and automated backup, reducing the risk of losing your data.

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

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

• Amazon QuickSight: 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.

• Echarts: This lightweight canvas library uses JavaScript and ZRender to offer highly customizable, interactive charts that you can add 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.

Key considerations in choosing visualization tools

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

It's important that the tool you select is 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.

Getting started with big data visualization tools on Coursera

Big data visualization tools can help you simplify vast amounts of data and present it in an easier way to understand and draw conclusions from. To effectively use data visualization, gain a basic understanding of data analytics with online courses on Coursera. You might consider an online course or Professional Certificate such as the Google Data Analytics Professional Certificate or the Google Business Intelligence Professional Certificate. Both of these programs cover data visualization fundamentals and, upon completion, offer a shareable certificate for you to showcase in your resume, CV, or LinkedIn profile.