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Data visualization tools play an essential role in data analytics by representing data in graphical form, including charts, graphs, sparklines, infographics, heat maps, or statistical graphs. Data presented in visual form is easy to understand and analyze, allowing even non-tech stakeholders to make more efficient real-time decisions.
Data visualization tools incorporate support for real-time and streaming data, artificial intelligence integration, collaboration, and interactive exploration to facilitate the visual representation of data. Many data visualization applications are cloud-based.
Data visualization supports data mining – indeed, some experts consider it to be a key data mining technique. Many of the leading data mining tools incorporate a data visualization feature.
Also see: Top Data Analytics Tools
Data visualizations present complex metrics in the context of visual relationships, enabling a faster and more intuitive approach to data mining.
How to Select the Best Data Visualization Tool
The market for data visualization tools is growing rapidly, which is driving the growth in solutions. Because of the complexity, businesses should speak with sales reps to gain a better understanding of how a given application meets their needs. Before the final decision is made, consider the following strategies when selecting data visualization software.
Research Pricing
Many data visualization tools are priced on a per user per month basis. Make sure to consider how many of your employees truly need access to these solutions, as every additional user typically costs more.
Alternatively, many solutions offer plans specifically tailored for larger enterprises. Be sure to consult various sales representatives to inquire about these options.
Decide on Your Use Cases
Once you’ve found solutions within your budget, consider what each solution can bring to the table in regards to your needs. There are three critical points to consider when selecting data visualization software:
1. Big Data
Data quantities are only growing. Moving forward, different approaches to business operations such as AIOps are available to manage these vast amounts of data. Until then, businesses should gain an understanding of how each data visualization software can help them aggregate and translate mass Big Data sets.
2. Data Tracking
When consulting with a sales representative, inquire about the various ways in which your desired software can track flaws and anomalies in data. Tracking links and similarities between data is also critical.
3. Scalability
Gaining an understanding of how each data visualization application can help with data sets and data tracking will generally reveal each solution’s potential for scalability. Still, be sure to dig into just how scalable a product truly is, and how providers can work with your business cost-wise as it continues to grow.
Best Data Visualization Tools
What follows is our top ten best data visualization tools, in no particular order:
- Tableau
- Microsoft Power BI
- Google Cloud
- Excel
- Sisense
- Zoho Analytics
- Google Charts
- FusionCharts
- Infogram
- Looker
- IBM Cognos Analytics
- Qlik
Tableau
Data visualization value proposition: Tableau is, without question, an industry leader. The team at Tableau emphasizes its usability for any and all users. This means that it is incredibly user friendly and built for a diverse amount of teams.
Tableau is by far the most popular data visualization tool, so much so that Salesforce bought it. Boosting its popularity, Tableau is accessible to everyone from college students to data scientists.
It’s an easy-to-use tool that provides results quickly, in a wide variety of formats. It provides integration with all of the major advanced databases, including Teradata, SAP, My SQL, Amazon AWS, and Hadoop.
Although Tableau is built for a wide range of users, it is still used for scalable, large enterprises. Some of its customers include Verizon, the WFP, and JPMorgan Chase & Co. If you’re planning on connecting with a sales representative at Tableau, be sure to inquire about their security as well as their integration capabilities.
Microsoft Power BI
Data visualization value proposition: Microsoft Power BI has been recognized as a leader in the 2021 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms for the past fourteen years. Much like Tableau, Power BI prides itself on its data-driven culture that’s open for all user types. One of the biggest advantages Power BI can bring for businesses is in its industry-leading AI.
Microsoft has two major visualization tools, with Power BI on the high end. It provides classic data visualization tool elements like interactive dashboards and APIs for integration and is tightly integrated with the Microsoft data platforms like SQL Server and Sharepoint.
It operates a lot like Excel, so if you have cut your teeth on Excel the learning curve is shorter. Still, Power BI comes with a slew of features that set it apart from its more ubiquitous counterpart. The standout point of Power BI is in its AI and machine learning (ML) capabilities. Microsoft AI is incorporated to allow non-data scientists to plan and build full machine learning models and quickly track insights from their data sets.
Plus, for teams working with Excel as well, Power BI integrates with Excel to publish data in more user-friendly, digestible formats.
Excel
Data visualization value proposition: Excel is one of the most affordable and no-frills data visualization tools available today. This makes it one of the best beginning tools for businesses, especially SMBs.
Beyond its primary use as a spreadsheet tool, Excel comes with very good basic data visualization tools and functions. It comes with 20 or more built-in charts, including pie charts, radar charts, histograms, scatter plots and more.
It’s a great beginner tool you probably already have, but it doesn’t scale well and if your data sets grow, you will likely want to upgrade to Power BI. Price-wise, Excel offers business plans for scaling companies, but at a monthly fee that also features tools like Microsoft Word, Powerpoint, and OneDrive.
Sisense
Data visualization value proposition: Sisense works with scaling businesses to integrate and track analytics in both their workflows and analytics products. It is primarily built for larger businesses and enterprises looking to sort through very dense and large data sets.
Sisense is a data visualization tool based on a business intelligence model that offers multiple tools for data analysis. The tool is pretty easy to set up and use, it can be installed in minutes and provides instant results, yet it has the advanced functionality seen in mature, high-end software like Tableau.
One of these features is in-chip processing which allows for faster, more efficient queries. It allows the users to export files in common formats like PDF, Word, Excel, and PowerPoint.
Sisense is no-code friendly. This means that insights can be extrapolated and complex models can be built by non-data scientists. Still, Sisense is built to be scalable across all skill levels and use cases. This radically opens up its usage for virtually an entire business. Again, this is yet another reason why enterprises should consider Sisense over SMBs or individuals looking for data visualization tools.
Zoho Analytics
Data visualization value proposition: Consider Zoho Analytics a similarly affordable alternative to Microsoft Power BI. Use cases are broad and scalability is very similar. Businesses should, however, inquire about Zoho Analytics’ AI and ML capabilities before moving forward.
Zoho Analytics also specializes in business intelligence visualizations, offering a number of different ways to chart your data and a variety of dashboards. It supports a broad number of different data sources and lets you prep your data within the platform.
Its real strength is an artificial intelligence assistant called Zia that lets you ask questions in natural language. Through conversational AI, users can ask Zia questions about insights and gain results instantaneously. Zia even provides smart suggestions as users type out their questions. Still, this use case is primarily built for non-data scientists and individuals in need of quick data. Zoho Analytics provides a number of advanced solutions for larger enterprises.
In fact, Zoho Analytics offers a large set of APIs for developers looking to tweak data integration, authorization, custom styling and more. Zoho Analytics has been used by companies such as HP, Hyundai, LaLiga, and Ikea for insight gathering and data visualization.
Google Charts
Data visualization value proposition: If you are an individual looking for a free charting solution and have coding experience, consider Google Charts. Other than this use case, we recommend businesses looking for data visualization software to look toward more scalable and AI-based solutions.
Google Charts lets you create interactive charts which include maps, bar charts, histograms and more. You can then embed these online and run them live. This is ideal for people who already use Google Workspace and want to integrate with many data sources.
Google Charts works with a wide variety of SQL databases and also has a number of data connectors for you to collect your data. On the downside, you need to know how to code to use it, which is likely a barrier for most beginners. And it isn’t as well supported as other products.
FusionCharts
Data visualization value proposition: FusionCharts is the much more flexible and scalable alternative to Google Charts. Still, solutions like Tableau or Power BI will be of more interest for enterprises in need of advanced, AI-driven data visualization and business intelligence.
FusionCharts is a JavaScript-based tool that offers more than 100 interactive charts and more than 2,000 maps, making it one of the most flexible tools out there. It also integrates with a number of other data visualization platforms, such as Angular, React, Vue, JQuery, PHP, Ruby on Rails, ASP.NET, Django.
While the software offers a large number of pre-set templates, it’s based in JavaScript, so you do have to know the language to make the most out of it. This means that it is not the most scalable solution skill-wise.
One of FusionCharts’ most helpful features is its accessibility when publishing charts. Charts work across all platforms, including desktops, tablets, and mobile phones. Charts are also touch optimized with no additional effort on the user-end.
Infogram
Data visualization value proposition: Infogram is a more user-friendly, graphic-design forward alternative to Google Charts and FusionCharts. It is not an advanced solution built for enterprises like Power BI and Sisense.
Infogram is popular for creating reports, charts and maps. Its strength is in generating infographics and comes with more than 550 maps and 35 interactive charts. It has an easy-to-use interface and the data visualizations are considered easy to learn.
Another point in its favor: it comes with many different templates with aesthetically pleasing designs. Although Infogram has been used by a multitude of industry leaders, its use cases are ultimately rather simple. If you’re in marketing, media, or in the nonprofit sector, Infogram is a good solution for simple social media engagement and graphic design solutions.
Looker
Data visualization value proposition: Looker pushes its flexibility as a standout point. Looker can integrate and adjust to any business workflow and is embeddable in a number of third-party systems. It also offers low-code solutions that allow non-data scientists to build their own applications.
Looker is a comprehensive business intelligence tool with links to Snowflake, Redshift, and BigQuery along with over 50 SQL dialects, so you can connect with several databases at once, then export your results in any format.
It offers a real-time dashboard for data analysis to help you make business decisions based on the data visualization. Furthermore, distribution of data reports, insights, sets, and query results can be scheduled and automated. Looker is used by a multitude of different business verticals, including eCommerce, media, ad-tech, SaaS, and healthcare.
IBM Cognos Analytics
Data visualization value proposition: Highly affordable and incredibly advanced, IBM Cognos Analytics is very effective for a multitude of enterprise uses. It also offers the same user-friendliness that alternatives like Power BI and Tableau offer for SMBs.
IBM Cognos Analytics is a cloud and on-premise-based business intelligence solution that uses an augmented intelligence-infused AI assistant that allows users to ask questions and get answers in natural language. It also recommends new visualizations and potential connections in data, allowing users to unearth connections they might not anticipate.
It offers users a wide range of business analytics functionality and a full complement of essential analytics functions, including advanced dashboarding, data integration, reporting, exploration and data modeling.
IBM Cognos can import data from CSV files and spreadsheets, and connect to a variety of data sources. This includes SQL databases, Google BigQuery, Amazon, and Redshift. Cognos also offers a mobile app where users and stakeholders can access data and get instantaneous alerts.
Qlik
Data visualization value proposition: Qlik’s approach to BI is to go beyond the idea of passive BI. Qlik’s primary approach utilizes the Qlik Active Intelligence Platform, which delivers real-time and up-to-date information that trigger immediate actions.
Qlik Sense is Qlik’s proprietary software, built primarily for users of all skill levels to build data models and track insights from their data sets. This no-code approach does not detract from its AI capabilities, though. Qlik features AI-generated analysis, automated data prep, and predictive analytics fueled through machine learning.
Qlik’s products are built to scale. This is true for its security and governance as well. Its platform can be deployed on a single server or scale to larger enterprise frameworks. This is true for on-premise or cloud networks. This means that Qlik is highly optimizable and will deliver high performance for growing data sets, all while maintaining a company’s security model.