10 Top Data Visualization Tools for 2022

Data science is gaining importance these days. Data visualization tools are all about gathering raw data and converting the same into visuals. Being visual creatures, viewers can find colorful graphics to be quite appealing. Businesses can also convey messages quite easily and more effectively unlike plain numbers.

Visuals also provide valuable information that can be absorbed effortlessly. It also helps specific datasets to become more appealing to users. Incorporating the same into business does not require any expertise. You just need to use the right tools and develop attractive charts, maps, diagrams along other visuals.

Top 10 Data Visualization Tools

1. Tableau Public & Gallery:

Pros:

• This software combines ease of use and versatility.
• Informative community
• Offers plenty of tutorials
• Easy to update
• Mobile responsive
• Easy data blending
• Extensive customer support
• Manual setup not required

Cons:

• Data analysis does not remain private
• Local saving of reports not allowed
• Auto-refresh as well as report scheduling options not offered

2. HockeyStack

Pros:

1. End-to-end SaaS-based analytics, machine learning
2. Unify product data, sales, revenue, and marketing into a single dashboard without any code.
3. No setup is required.
4. Allows visually appealing, customized dashboard creation to answer queries related to inter-departments.
5. Surveys, segments, revenue analytics.

3. Google Charts:

Pros:

• User-friendly platform
• Cross-browser compatible
• Google product and cloud computing compatibility
• Easy import of data from SQL databases, Salesforce, Google Fusion Tables, and Google Spreadsheets.
• Mobile-friendly
• Interactive dashboard
• Manages huge datasets
• Displays real-time and live data on-site.

Cons:

• Require optimization of exporting tools
• Support not offered for Google Charts
• Sophisticated statistical processing is not present.

4. Google Data Studio

Pros:

• Free AI integration features
• SQL knowledge is not desired.
• Easy to use and intuitive
• Integrates well with Google’s ecosystem
• Data can be merged within a single report derived from multiple sources
• Interactive and dynamic visual analytics

Cons

• Lacks basic calculations
• Excel files not supported
• Lacks on-premise option essential for security

5. Infogram

Pros:

• This machine learning offers easy UX to non-designers.
• Intuitive drag-drop editor
• Includes 550+ maps and 35+ chart types along with infographics
• Easy embedding and exporting options for private/public outlets
• API to import additional data sources

Cons

• This data science tool has fewer integration features and inbuilt sources.
• Rich text editing is not provided with the free plan
• Modification desired in customer support

6. Datawrapper:

Pros:

• Maps, tables, and charts can be exported as PNGs.
• Installation not necessary
• Inbuilt color blindness checker
• Mobile-friendly
• Auto-save feature
• Coding skills are not necessary

Cons:

• This cloud computing tool focuses on the journalism industry alone.
• Customizations not offered

7. D3.js

Pros:

• Customizable, fast, and powerful
• Even non-programmers can use this visual analytics tool to develop visualizations.
• Focuses on embedding and standards
• Can visualize data in HTML, CSS, and SVG

Cons:

• Data-source restrictions
• Cannot conceal easily original data.

8. Flourish Public

Pros:

• Ready-to-use templates
• Mobile-friendly previews offered
• Resources offered.
• Published projects will work even if an account is closed

Cons:

• Visuals appear with Flourish branding.
• Imports possibly only with CSV and Excel files

9. RAWGraphs:

Pros:

• Simple interface
• Mobile-friendly AI integration tool
• Cloud-based
• Re-arrangeable and easy-to-read visual layout
• Assures data security

Cons:

• Managing huge data sets involves problems
• Data parameter issues
• Dynamic or interactive visuals cannot be created
• Log scales are not offered

10. Dygraphs

Pros:

• Interactive out-of-the-box: pan, zoom, and mouseover are offered by default.
• Manages huge data sets and multiple data series
• Mobile-friendly
• Works with all recently launched browsers.
• Highly customizable

Cons:

• Visuals available publicly
• Needs on-pre setup
• Tough to navigate site and filled with bugs
• Import sources restricted to DataTable, function, array (native format), URL, CSV data

The above-given Data Visualization Tools can break down data, thereby making it quite easy to understand.