Top Datascience Visualization Tools of 2022
I break down some of the top tools
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So let’s get into it:
Data Visualization is one of the most important part of data analysis. It has always been important to present the data in an understandable and visually appealing format.
Weekend Poll
Which do you think is the most important skill to master in datascience? See my on-going poll on this on LinkedIn here. Clearly data visualization tools rank high on that list of foundational skills for data scientists.
Top Visualization Tools of 2022
So what are the latest data visualization tools that every data scientist can use to make their work more effective? In an era where A.I. needs to become more explainable, the way we visualize data is key. To be a data centric society will require even more data scientists, programmers and data engineers.
According to a Fortune Business Insights report, the data visualization market in 2019 was estimated at $8.85 billion. By 2027, the market worth is expected to be $19.20 billion at a compound annual growth rate of 10.2%.
The Evolution of Data Visualization
Why it Matters?
Data presented through visual elements is easy to understand and analyze, enabling the effective extraction of actionable insights from the data. Relevant stakeholders can then use the findings to make more efficient real-time decisions.
Data visualization tools, incorporating support for streaming data, AI integration, embeddability, collaboration, interactive exploration, and self-service capabilities, facilitate the visual representation of data.Â
In this article I hope to introduce you to a variety of different visualization tools that are now being used and perhaps one of two you may not have heard of. So let’s get into it:
1. Tableau
And still #1.
If you never heard about this fabulous tool then you are probably very new to data visualization. Tableau is a data visualization tool founded in 2003 that focuses entirely on visual analysis with the ability to analyze any kind of data and transforming it into hundred of representation graphs and maps allowing you to get better insights into your data. For the most part this tool is aging well. In 2022, more than 57,000 companies use Tableau.
Key features of Tableau:
Tableau is known as the simplest business intelligence tool for data visualization
Data scientists do not need to write custom code in this tool
The tool is also a real-time collaboration along with data mixing
The Pros of Tableau:
Excellent visualization capabilities
Easy to use
Top class performance
Supports connectivity with diverse data sources
Mobile Responsive
Has an informative community
The Cons of Tableau:
The pricing is a bit on the higher side
Auto-refresh and report scheduling options are not available
2. D3
D3.js is a JavaScript library for producing dynamic, interactive data visualizations in web browsers. It makes use of Scalable Vector Graphics, HTML5, and Cascading Style Sheets standards.
The tool was initially released on Feb 18, 2011, and became official in August.
It supports HTML, CSS, and SVG. Developers can present data in the form of creative pictures and graphics. It is a very flexible platform as it allows variations for the creation of different graphs.
Key features of D3:
This data visualization tool offers powerful SVG operation capability
D3 integrates multiple methods as well as tools for the processing of data
Data scientists can effortlessly map their data to the SVG attribute
3. Dundas BI
Dundas Data Visualization, Inc. is a software company specializing in data visualization and dashboard solutions.
Dundas BI offers highly-customizable data visualizations with interactive scorecards, maps, gauges, and charts, optimizing the creation of ad-hoc, multi-page reports. By providing users full control over visual elements, Dundas BI simplifies the complex operation of cleansing, inspecting, transforming, and modeling big datasets.Â
The Pros of Dundas BI:
Exceptional flexibility
A large variety of data sources and chartsÂ
Wide range of in-built features for extracting, displaying, and modifying data
The Cons of Dundas BI:
No option for predictive analytics
3D charts not supported
4. JupyteR
A web-based application, JupyteR, is one of the top-rated data visualization tools that enable users to create and share documents containing visualizations, equations, narrative text, and live code. JupyteR is ideal for data cleansing and transformation, statistical modeling, numerical simulation, interactive computing, and machine learning.Â
The Pros of JupyteR:
Rapid prototyping
Visually appealing results
Facilitates easy sharing of data insights
The Cons of JupyteR:
Tough to collaborate
At times code reviewing becomes complicated
5. Microsoft Power BI
This is another one that has aged well.
Power BI is an interactive data visualization software product developed by Microsoft with primary focus on business intelligence. Its first release was in 2014.
It is a set of business analytics tools that can simplify data, prepare and analyze instantly. It is the most preferred tool as it can easily integrate with Microsoft tools and is absolutely free to use and download.
The tool is available for both mobile and desktop versions. So if a business uses Microsoft tools it can be a big benefit for them.
Key features of Microsoft Power BI:
Generate interactive data visualizations across multiple data centers
It offers enterprise data analytics as well as self-service on a single platform
Even non-data scientists can easily create machine learning models
6. Zoho Reports
Zoho Analytics is a self-service BI and data analytics software that lets you analyze your data, create stunning data visualizations, and discover hidden insights in minutes.
Zoho Reports, also known as Zoho Analytics, is a comprehensive data visualization tool that integrates Business Intelligence and online reporting services, which allow quick creation and sharing of extensive reports in minutes. The high-grade visualization tool also supports the import of Big Data from major databases and applications.Â
The Pros of Zoho Reports:
Effortless report creation and modification
Includes useful functionalities such as email scheduling and report sharing
Plenty of room for data
Prompt customer support.
The Cons of Zoho Reports:
User training needs to be improved
The dashboard becomes confusing when there are large volumes of data
7. Datawrapper
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This tool is a blessing for non-technical users and is the most user-friendly visualization tool. To create visualizations you need to have technical skills such as coding but in this app, you don’t need to have any technical skills.
The app can be best used by beginners who want to start their career in data visualization. This app is the most user-friendly app for a data scientist. The tool is widely used in media organizations where there is a high need for presenting everything through stats and graphs. The tool is the most popular choice because it has a simple and easy interface.
Key features of Datawrapper:
It offers the users with an embed code and provides the ability to export charts as well
Option to select multiple map types and charts at once
The tool requires no advanced knowledge of coding for its installation
Honorable Mention
Visual.ly: https://visual.ly/
Google Charts: https://developers.google.com/chart
E-Charts: https://echarts.apache.org/en/index.html
Plotly: https://plotly.com/
RAW: https://rawgraphs.io/
Whatagraph: https://whatagraph.com/
SiSense: https://www.sisense.com/
QlickView: https://www.qlik.com/us/
FusionCharts: https://www.fusioncharts.com/
IBMWatson: https://www.ibm.com/analytics/data-visualization
Wolfram Alpha: https://www.wolframalpha.com/
Which data visualization tool do you find yourself using the most in the field? Leave me a comment.
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