Top 20 Data Visualization Tools for Digital Marketers

Images are a great way to express rather, human brains process visuals 60,000 times faster than they do text.

Data is indeed everything in the present world. With tons of data available on almost everything, it becomes a very difficult task to analyze it efficiently. That is where data visualization helps to convert this data into a visual representation. Visual representations of the data make it easy for people to understand and analyze it. 

But someone has to collect and segregate all the data to transform it into a visual form. And the task is accomplished by the data visualization team. They are humans, too, dealing with enormous data is a time-Consuming and hectic task for the team; that is where various data visualization tools come into play. 

What are Data Visualization Tools?

Data visualization technologies make it easier for data visualization designers to create visual representations of large data sets. When working with data sets with hundreds of thousands or millions of data points, automating the visualization process makes a designer’s job easier, at least in part.

This data visualization can be used in dashboards, annual reports, sales and marketing materials, investor presentation decks, and practically anywhere else where information needs to be processed rapidly.

The Importance of Data Visualization Tools

When information is visualized, it is easier to comprehend. Visualization aids in communicating a story to decision-makers in a corporate setting, allowing them to respond faster than if the information were presented in reports. By employing data visualization tools to communicate their findings better, data scientists can better share their ideas with individuals who are unfamiliar with data science themes.

How to Find the Right Data Visualization Tools?

When it comes to choosing a data visualization tool, there are a few things to keep in mind.

• Stability vs Flexibility: Simple to Operate

Flexible visualization tools come with a long list of features that provide you with entire configuration control, fine-grained visualization design changes, and advanced analytical capabilities. Because of the emphasis on ease of use, non-technical persons may get started quickly.

• Data Storytelling/Explanation vs Visual Analytics/Exploration

Data analysis becomes faster and more capable with the use of visual analytics tools. Patterns emerge from the visualizations, allowing the analyst to explore deeper into the data.

The goal of data storytelling tools is to make it easier for individuals to share data with one another. The user wishes to send a message or information to a specific group. To tell the whole tale, the data might be merged with other data and visualizations.

• Independent Visualizations vs Applications/Dashboards

Independent data visualization tools can make only one chart at a time. Each graphic is its own “island” with its own data set. Graphs like these are typically part of a separate website. Application and dashboard development tools are the basic building blocks for creating an app or a dashboard. You’re creating a group of graphic components that work together to cover a greater range of data in this scenario.

• Broad Data Platforms vs Focused Visualization Tools

Complex data platforms will emphasise visualization elements as an entry point for new users. These platforms could include a variety of data management, governance, and modelling capabilities. Solutions that focus on visualization tend to stick to their strengths. These solutions, in particular, do not claim to be the “one source of truth” for data in an organization.

• Cost to Get Started

Free with limitations on volume of use or advanced features. 

Benefits of Data Visualization Tools

Data visualization can help decision-makers increase data insights in a variety of ways when it comes to corporate aims and goals. 

1. Practical Data Visualization can unlock the potential of Big Data. It can swiftly and easily take in vast volumes of data that are shown in visual representations, and any data inefficiencies can be corrected.
2. By helping users immediately understand data, visualization may Considerably speed up decision-making. Any organisation must have the capacity to react swiftly and avoid letting inefficiencies drag it down. One can profit from any market situation by acting quickly to avert losses.
3. An important disclosure of any differences in trends and patterns is necessary for any organisation to survive. It is essential to understand what is causing bigger losses or what is required to maximise gains.
4. Visualization enables the rapid detection of data errors and inaccuracies.
5. A visualization is a powerful tool that businesses may utilise to gain real-time information and greatly aid in management duties. Decision-makers can use on-demand data and visualization to improve operational performance and increase productivity.
6. It promotes narrative most effectively. Visuals are the most efficient way to convey the desired message to the audience.
7. Data visualization makes it easy to explore business insights to drive corporate goals correctly. It is useful to correlate the data from graphical or visual representations. It allows for speedy analysis and quickly assimilates important metrics.
8. Data visualization tools help organisations stay competitive by seeing the newest trends.
9. Businesses would have to put in a lot of work to change dashboards, produce reports, and respond to ad hoc demands if data visualization weren’t available. Data optimization and quick data retrieval through customised reports are two advantages of data visualization technology, which significantly cut down on employee time.

Comparison of Top 20 Data Visualization Tools

The Data Visualization tools, without a doubt, are of great benefit to data scientists. Here are the top 20 data visualization tools that can help you:

Top 20 Data Visualization Tools

1. Tableau (and Tableau Public)

Tableau is one of the best data visualization tools that provides a desktop programme, server and hosted web versions, as well as a free public alternative. It provides various options to import the data CSV files, Salesforce data,  and Google Ads and Analytics data, etc. 

😍 Pros

• There are a plethora of data import options to choose from.
• Map-making abilities
• There is a free public version accessible.
• There is a slew of video tutorials available that teach you how to use Tableau 

😢 Cons

• In the public version, you can’t keep data analysis secret.

💰 Pricing

2. Infogram

Infogram is a drag-and-drop data visualization tool for marketing reports, infographics, social media postings, maps, dashboards, and more than even non-designers can use.

😍 Pros

• There are a variety of Pricing options available, including a free plan with limited features.
• There are over 35 different chart kinds and 550 different map types to pick from.
• A drag-and-drop editor API can be used to import other data sources.

😢 Cons

• There are much fewer built-in data sources than in other programmes.

💰 Pricing

3. ChartBlocks

ChartBlocks’ is one of the best data visualization tools that allow data to be imported from “anywhere,” including live streams, according to the business. While they promise that data can be imported in “a few clicks” from any source, it’s likely to be more complicated than other apps with automated modules or extensions for specific data sources.

😍 Pros

• Both free and reasonably priced premium choices are available.

😢 Cons 

• The wizard for importing essential data is simple to utilise.
• Their API’s dependability is unknown.
• There doesn’t appear to be any mapping functionality.

💰 Pricing

4. Datawrapper

Datawrapper is one of the data visualization tools created specifically for the purpose of adding charts and maps to news stories. The produced interactive graphs and maps can be embedded on news websites. However, their data sources are limited, therefore copying is the most common method.

😍 Pros

• Designed primarily for data visualization in newsrooms.
• For small websites, the free plan is appropriate.

😢 Cons

• There is a built-in colour blindness checker in the tool.
• The number of data sources available is restricted.
• The paid plans are a little on the expensive side.

💰 Pricing

5. D3.js

D3.js is a JavaScript toolkit for manipulating data-driven documents. D3.js requires at least a basic understanding of JS, although there are apps available that make the framework accessible to non-programmers.

😍 Pros

• Very adaptable and potent.
• There are many different sorts of charts to pick from.
• The importance of web standards cannot be overstated.
• These tools can be used to create visualisations by people who aren’t programmers.

😢 Cons

• You’ll need to know how to programme it to use it on your own.
• In comparison to commercial tools, support is limited.

💰 Pricing

6. Google Charts

Google Charts is a powerful, is one of the free data visualization tools for creating interactive charts for web embedding. It uses dynamic data, and all of the outputs are HTML5 and SVG, so no additional plugins are required to view them in browsers. Among the data sources are Google Spreadsheets, Google Fusion Tables, Salesforce, and other SQL databases.

😍 Pros

• There are numerous free chart types available.
• It is cross-browser compatible due to the use of HTML5/SVG.
• makes use of dynamic data

😢 Cons

• Outside of the lessons and forum, little assistance is offered.

💰 Pricing

7. FusionCharts

FusionCharts is another JavaScript-based data visualization tools for creating online and mobile dashboards. It features 1,000 different map types and about 150 different chart types. Both server-side programming languages and popular JS frameworks (including React, jQuery, React, Ember, and Angular) can be integrated with it (including PHP, Java, Django, and Ruby on Rails).

😍 Pros

• There are numerous chart and map formats to choose from.
• This visualization tool has more features than the majority of others combined.
• Its compatibility with various programming languages is a big benefit of FusionCharts.

😢 Cons

• Developer licences are expensive (about $500 for one).
• This is excessive for straightforward visualisations outside of a dashboard setup.

💰 Pricing

8. Chart.js

A straightforward yet adaptable JavaScript digital visualization tools Chart.js. It features eight different chart kinds, supports animation and user interaction, and is open source.

😍 Pros

• Free and open-source Cross-browser compatibility and responsive output

😢 Cons

• Compared to other tools, very few different chart types are available.
• A lack of assistance beyond what is expressly stated in writing

💰 Pricing

9. Grafana

Grafana is a free and open-source visualization tools that allows users to build dynamic dashboards and other visualisations. It supports numerous data sources, annotations, and customizable alert features and may be enhanced utilising the tens of thousands of plugins that are readily available. As a result, it ranks among the most effective visualization tools available.

😍 Pros

• Both free and commercial versions of open source are available.
• There are numerous data sources accessible.
• There are many different sorts of charts.
• facilitates the creation of dynamic dashboards capable of handling various data inputs.

😢 Cons

• Simple visuals with added complexity have fewer options for aesthetic customization than some other programmes.
• The absolute worst option for creating visualization images
• Individual panels can be integrated in websites, but dashboards cannot.

💰 Pricing

10. Chartist.js

The free, open-source JavaScript data visualization tool Chartist.js may be used to create straightforward, responsive charts that are highly customizable and cross-browser compatible. The entire JavaScript library only uses 10KB when GZIPped. Plugins can be used to enlarge and animate Chartist.js charts.

😍 Pros

• Free and open source
• little file size
• Charts can be animated.

😢 Cons

• There is not the widest selection of chart kinds available.
• Absence of mapping capabilities
• There isn’t much support available outside of the developing community.

💰 Pricing

11. Sigmajs

A specialised data visualization software is called Sigmajs. It is extremely customizable, although utilising it does require some knowledge of JavaScript. The resulting graphs can be embedded and are dynamic and interactive.

😍 Pros

• Incredibly flexible and extensible
• Apps and websites can quickly incorporate free and open source graphs.

😢 Cons

• provides only one type of visualisation: network graphs, which must be customised and implemented using JS.

💰 Pricing

12. Polymaps

Polymaps is the name of a particular JavaScript mapping library. The end result is a set of responsive, dynamic maps in a variety of forms, including overlays for images and density maps. Since the images are created with SVG, designers can modify the maps’ visual appearance using CSS.

😍 Pros

• Free and open source
• Aiming towards mapping when designing
• embedding a simple map in apps and websites

😢 Cons

• The production of merely one type of visualization necessitates the use of sophisticated coding techniques.

💰 Pricing

13. Dundas BI

Dundas BI makes it simpler to build ad hoc multi-page reports by offering highly customizable data visualisations including interactive scorecards, maps, gauges, and charts. By giving users total control over visual elements, Dundas BI simplifies the challenging process of cleaning, evaluating, manipulating, and modelling huge datasets.

😍 Pros

• Graphs and data from a variety of sources
• numerous integrated tools for accessing, examining, and altering data

😢 Cons

•  lack of a predictive analytics tool and the inability to support 3D visuals.

💰 Pricing

14. Jupyter

Users can create and share documents with visuals, equations, narrative prose, and live code using JupyteR, one of the most well-liked web-based apps for data visualisation. JupyteR is the best tool for statistical modelling, numerical simulation, interactive computing, and machine learning.

😍 Pros

• The ability to share data insights with ease is made possible by good-looking results.

😢 Cons

• interaction is challenging
• Sometimes, code review can be difficult.

💰 Pricing

15. Zoho Reports

The integrated business intelligence and online reporting capabilities of Zoho Reports, also known as Zoho Analytics, make it simple to create and distribute detailed reports in just a few minutes. The premium data visualization tool now supports Big Data input from big databases and apps.

😍 Pros

• Ease of report creation and modification.
• Offers useful components like email scheduling and report sharing
• It can accommodate an enormous amount of data.
• Fast client assistance

😢 Cons

• The dashboard becomes confusing when there is a lot of data.

💰 Pricing

16. Visual.ly

Visual.ly, one of the data visualization tools now accessible, is well-known for its impressive distribution network that shows project results. By utilising a dedicated creative team for data visualization services, Visual.ly streamlines the process of data input and outsourcing, even to third parties.

😍 Pros

• Excellent images are simple to develop
• numerous choices for linking

😢 Cons

•  integrating options 
• Showcases only one point, not multiple.
• limited range

💰 Pricing

17. RAW

The delimited data formats TSV and CSV are supported by RAW, also known as RawGraphs. It acts as a bridge between spreadsheets and data visualization. Even though RawGraphs is a web-based application, it offers strong data protection and a variety of unconventional and standard layouts.

😍 Pros

• Exceptionally swift visual feedback provides a complicated system for organising, storing, and accessing user input.
• Excellent visual graphics readability and an intuitive mapping function
• Excellent scalability option

😢 Cons

• absence of log scales.
• unclear right away

💰 Pricing

18. IBM Watson

Watson is a world-class data visualization tool that uses analytical tools and artificial intelligence to uncover patterns and insights in both structured and unstructured data. Watson is named after Thomas J. Watson, the founder of IBM. Natural Language Processing is used by IBM Watson’s intelligent, self-service visualization tool to guide users through the entire insight discovery process (NLP).

😍 Pros

• NLP capabilities include access through a range of devices.
• Future forecasting analytics
• self-service dashboards

😢 Cons 

• Potentially better customer service; expensive upkeep

💰 Pricing

19. Sisense

Sisense, one of the most flexible platforms for data visualisation, enables users to access real-time data analytics from any location at any time. To assist decision-makers in making data-driven decisions, the top-of-the-line visualization tool may highlight major data trends and condense numbers.

😍 Pros

• Excellent client service, dependable interface, swift advancement, and flexible, seamless customisation make it ideal for crucial, large-scale projects.

😢 Cons

• It could be difficult to create and manage analytical cubes.
• not suitable for time formats
• There are several limited visualization techniques.

💰 Pricing

20. Qlikview

Qlikview, a leader in data visualization, provides solutions to more than 40,000 clients in 100 countries. In addition to offering rapid, customised representations, the Qlikview data visualization tool provides various valuable functions, including analytics, corporate reporting, and business intelligence capabilities.

😍 Pros

• favourable user experience
• beautiful, lively images
• Effective maintenance
• a cost-effective response

😢 Cons

• RAM limitations
• poor customer service
• excludes the drag-and-drop feature

💰 Pricing

Conclusion

The availability of tools for data visualisation has been a huge help to data scientists. With the help of data visualisation technologies, it was possible to manage massive amounts of information by means of a graphical representation. Every data visualization tool has something to offer. After examining your needs, choose the tool that provides the greatest solution for meeting those objectives with your data.

FAQs

Q. What are data visualization Tools?

A: A data visualisation tool is a way of displaying data so that it is easier to interpret. This could include charts, maps and diagrams. Data visualisations are extremely useful in a variety of fields including finance, politics, marketing, and healthcare.

Q: What mistakes are done frequently when visualising data?

A: When employing data visualization, it’s important to avoid misleading color contrast. Color is one of the most potent design components. Biased written descriptions, excessive data, missing baselines, scaling down, inappropriate visualization method, muddled relationships, focusing on favourable data, improper usage of 3D visuals, etc.

Q: How Can Data Be Visualized Effectively?

A: The data and its patterns should be accurately reflected in the display. It must be simple to understand what you are visualising. After seeing your visualisation, the reader should be able to take the appropriate action. Your message should be immediately grasped, to put it briefly.

Q: What are the three Considerations you need to make when choosing your data visualization objective?

A: There are three questions you should ask yourself when producing data visualisations.

• Does your graph offer an interesting conclusion? 
• Is your graph true to form? 
• Is the new information in your graph explained in detail?

Q: What are the four stages of data visualization?

A: These steps are exploration, analysis, synthesis, and presentation.