Data Visualization Tools
In many operations, the value of data has changed dramatically in recent years. For example, companies can now track the location of their vehicles and goods at any time, in real time. This was not possible a few years ago, and with data visualization tools, you can easily convert the information into a more comprehensive and understandable picture.
There are many ways to effectively communicate data to an audience, but one of the most efficient ways to do so is to use data visualization. With the help of these tools, it becomes easier for a data scientist to unfold the information hidden behind complex data and convey the same in a simplified manner.
Some common ways to visualize data include bar charts, line graphs, and scatter plots. It is important to choose the right visualization method for the data being analyzed and the question being asked.
What is Data Visualization?
Data visualization is the process of transforming data into a graphical format. It helps in creating visual representations of data to make it easier to understand and draw inferences. This can be done using a variety of methods and tools, including charts, graphs, and maps. This allows people to quickly see patterns and trends in data. Several benefits of using data visualization tools like simplifying complex data make it easier even for a technically night person to understand the information hidden in the data as well as present it in a more effective manner.
What is Data Visualization Tools?
Data visualization simplifies the representation of data and data visualization tools plays an integral role in this. These tools are designed to assess the data, derive useful inferences, and make it more relevant to the user. When you are dealing with voluminous data, manual assessment is challenging and can be misleading sometimes, so you have the best data visualization tools that simplify the process for the user.
Key benefits of using top data visualization tools:
- Helping to make sense of large and complex data sets
- Allowing for the identification of patterns, trends, and relationships
- Facilitating communication and understanding among team members
- Supporting decision-making
- Improving efficiency and productivity
What’s common among all the Data Visualization Tools?
Although there are different data science tools their prime objective is the same and that is to unfold the meaning hidden behind complex data. Hence all these tools have one thing in common, which is their objective to unveil the information and presented it in a comprehensible manner. No matter which tool you choose, data visualization can be a powerful way to see and understand data.
Data visualization tools convert the information into graphs, charts, or other visual representations. Data scientists use these tools to create static and non-static visualization. Static visualizations are images generated from data that do not change when the data changes. Interactive visualizations are visualizations that change when the data changes.
There are many different data visualization tools available. Some data visualization tools are designed for specific types of data, while others are designed to be more general. Data visualization tools are also designed to be used with specific software applications.
Top Data Visualization Tool List
1. Tableau –
It is an online data visualization software application that can be used to create a variety of static and interactive visualizations. Tableau includes a number of features for visualizing data. It is a business intelligence tool that helps organizations visualize and analyze their data. It offers a variety of features and benefits, but also has some drawbacks.
Key features of tableau
- A tabular format for data
- Can be used to present information in a more organized and readable way
- Allows for easy comparison of data
- Can be used to spot trends and patterns
- It offers a variety of features and benefits
- Helps organizations visualize and analyze their data
- Can be used to create dashboards and reports -Is easy to use and learn
- It can be expensive
- Requires a good understanding of data to be used effectively
- May not be suitable for all organizations
2. Google Sheets –
Google Sheets is a spreadsheet application that runs on the web. It is a part of the Google Docs suite of productivity tools, including Google Docs and Google Slides. Google sheets can be used for a variety of purposes, such as creating a budget, tracking expenses, and organizing data.
Key features of Google Sheets
- Create and edit spreadsheets directly in your web browser
- Sheets automatically save your work as you type
- Create, edit, and collaborate with others on spreadsheets from your computer, phone, or tablet
- Access, create, and edit your spreadsheets wherever you go — from your phone, tablet, or computer
- Get stuff done anytime, anywhere with Sheets
Pros and cons Google Sheets
- Easy to use
- Familiar interface
- Limited features and customization options
- No offline access
3. Microsoft Excel –
Excel is a spreadsheet application that is part of the Microsoft Office suite of productivity applications. Excel can be used to store, organize, and analyze data.
There are many ways to use Excel as a data visualization tool. One way is to use the built-in charts and graphs to create visualizations. Another way is to use the data in Excel to create custom visuals using the Visual Basic for Applications (VBA) programming language.
Key features of Microsoft Excel
- The user can store, organize, and analyze data.
- It comes with built-in features that make it easy to enter and manipulate data.
- This data visualization tool is loaded with powerful data analysis features that can be used to discover trends and relationships in data.
- Excel is a versatile program that can be used for various tasks, from simple data entry to complex data analysis.
Pros and cons of Microsoft Excel
- Very versatile and can be used for a variety of purposes
- Can be customized to suit individual needs
- Allows for complex data analysis and manipulation
- Can be integrated with other software programs
- Can be difficult to learn and use
- May be slow on older computers
- Some features may be locked behind a paywall
4. Infogram –
Infogram is an easy-to-use, cloud-based tool that lets you create stunning infographics, share them on social media, and embed them on your website.
It offers an extensive library of templates to help you get started, and you can customize your design to fit your brand. You can also access data from over 500 data sources, including Google Sheets, Excel, and CSV files.
Infogram is a data visualization tool for free use, but a paid plan gives you access to more features, including custom branding and extended data storage.
Key features of Infogram
- Infogram is a free online tool that allows users to create interactive charts, maps, and infographics.
- It has many features that allow users to customize their charts and infographics, including the ability to add videos, images, and links.
- You can take the paid subscription to access more features, like creating private charts and infographics and downloading high-resolution images.
Pros and cons of Infogram
- Free to use
- Many customization options
- Can add videos, images, and links
- Paid subscription gives access to more features
- Includes a wide range of templates and charts
- Features an easy-to-use drag-and-drop interface
- Limited features for free users
- Paid subscription can be expensive
ChartBlocks is a cloud-based charting tool that allows users to create, share, and embed interactive charts and graphs. It offers a free and paid plan, with the paid plan offering more features and options.
Key features of ChartBlocks:
- ChartBlocks is designed to be easy to use, even for those with no prior experience in creating charts and graphs.
- It is flexible enough to allow users to create a wide variety of charts and graphs.
- One can easily customize using this tool, thus, it allows users to change the look and feel of their charts and graphs.
- ChartBlocks charts and graphs can be exported to a variety of formats, including PNG, JPEG, and PDF.
Pros and cons of ChartBlocks
- Easy to use
- Can create charts and graphs without any coding
- Free plan available
- Can share charts and graphs online or embed them on websites
- Limited features and options on the free plan
- The paid plan is required to unlock all features and options
6. Datawrapper –
Datawrapper is a tool for creating interactive charts and maps. It lets you upload your data and create a visualization, which you can embed on your website or blog. The visualizations are responsive, meaning they will resize to fit the containing element’s width.
Datawrapper is free to use and open source. It has a paid version with more features, but the free version is more than adequate for most uses.
It offers a wide range of visualization types, including bar charts, line charts, pie charts, scatter plots, and more. This makes it easy to find the right visualization for your data.
There is no fuss when it comes to using this software. Even for users unfamiliar with data visualization. The interface is intuitive, and it is easy to create a visualization.
Key features of Datawrapper
- It allows the user to share visualization via email, social media, or embedded on a website or blog.
- Ease of customization is yet another feature that gives the user leverage to create output as per specific requirements.
- Datawrapper is a very affordable option for data visualization, with plans starting at just $9 per month.
Pros and cons of Datawrapper
- The visualizations are stunning and interactive.
- DataWrapper makes it easy to upload data from Excel, Google Sheets, and CSV files.
- Embed visualization on websites and blogs.
- DataWrapper offers a free plan for up to five visualizations per month.
- Paid plans start at $19 per month and include unlimited visualizations.
- DataWrapper has a user-friendly interface that makes creating visualizations quick and easy.
- One can customize it to meet your specific needs.
- It offers excellent customer support.
- The user can integrate it with Tableau, Google Analytics, and other data visualization tools.
- DataWrapper is constantly adding new features and improvements.
7. Polymaps –
The library is designed to be small and simple, yet still provide a powerful API. The library focuses on providing a basic set of features, so it does not include all of the bells and whistles that you find in other mapping libraries.
Some of the features of Polymaps include:
- It supports multiple map types (Google Maps, Bing Maps, etc.)
- Polymaps is compatible with multiple data formats (KML, GeoJSON, etc.)
- It supports multiple projection types (Mercator, Orthographic, etc.)
- It has a simple API for creating and interacting with maps
Pros and Cons of Polymaps
- Allows you to display data on a map in a very visually appealing way
- Is interactive- users can hover over data points to see more information
- You can use it to display a variety of data types
- May be difficult to set up if you are not familiar with coding
- Limited to display data that can be mapped geographically
Grafana is a data visualization tool that allows you to create dashboards and charts to visualize data from a variety of data sources. It is one of the best data visualization tools open source that is distributed on the AGPL 3.0 license
Grafana is a data visualization and monitoring solution that allows you to query, visualize and alert on data collected in Prometheus. It can also be configured to take data directly from other data sources, such as an InfluxDB database.
Grafana is a popular open-source visualization tool that can be used on top of a variety of different data stores but is most commonly used together with Graphite, InfluxDB, Prometheus, Elasticsearch, and Logz.io.
Grafana allows you to query, visualize, alert, and understand your metrics no matter where they are stored. Create, explore, and share dashboards with your team and foster a data-driven culture.
Key features of Grafana:
- A rich set of panel types including graph, table, gauge, heatmap, and more
- An intuitive and powerful query editor
- The ability to combine multiple data sources on the same dashboard
- A flexible and responsive layout that adapts to any screen size
- A built-in alerting engine with email, Slack, and PagerDuty notifications
- An easily extensible plugin architecture
- Some of the big names in the business worl Cisco, Dell, eBay, IBM, Microsoft, Paypal, and Slack rely on Grafana
Pros and cons of Grafana
- Grafana is open-source and free
- It is easy to install
- It has a large user community
- There are many plugins available
- Grafana is highly customizable
- The user can share the dashboard
- Grafana dashboards can be difficult to understand for those who are not familiar with them
- It requires a fair amount of setup and configuration
- It is not compatible with a few monitoring tools, so there may be less support available
9. Fusioncharts –
FusionChart is a cross-platform and cross-browser charting solution. One can create interactive charts for web, mobile, and desktop applications using it. It offers a wide range of features that make it a powerful and flexible tool for data visualization.
Key features of FusionChart:
- FusionChart can be used to visualize data in various ways with the help of interactive and customizable chart types
- It has rich API which allows developers to create custom applications and integrations.
- It offers cross-platform and cross-browser compatibility.
- FusionChart is compatible with many platforms and browsers, making it a versatile solution for data visualization.
- FusionChart can be used with various data sources, including relational databases, XML, JSON, and CSV files.
- It offers a flexible licensing model that allows developers to choose the features and functionality they need.
Pros and cons of FusionChart:
- It is a very powerful and flexible tool that can create various charts and graphs.
- Using FusionChart is easy
- A wise array of options and settings allow you to customize the appearance of your charts.
- You can use the free trial to try out the software
- It can be expensive
- Incompatibility with all web browsers.
- Using this tool is a bit challenging task
How Data Visualization Tools Can Boost Your Career?
Data visualization has come a long way in the last few years. These tools help the data scientist and analyst to easily turn data into information and pictorial representation which is better decision-making. However, data visualization is not just for analysts and managers. In today’s data-driven world, data visualization is a valuable skill for anyone who wants to further their career.
Data visualization is a key tool for data scientists, allowing them to effectively communicate their findings to both technical and non-technical audiences. By visualizing data, data scientists can better understand complex relationships and patterns, identify trends and outliers, and communicate their findings in a more accessible and engaging way.
Read More 📜📜 Data Visualizations in Python and R
FAQs – Data Visualization Tools
What is Data Visualization?
There is no one answer to this question as data visualization can mean different things to different people. Still, data visualization generally refers to taking data and representing it in a graphical or visual format. You can do this in various ways, such as through charts, graphs, maps, or other visual representations.
What are the best data visualization tools?
There are several data visualization tools but when it comes to the best one then you can consider:
- Google Charts
- Microsoft Power BI
- Microsoft Power BI
- Google Data Studio
What are data visualization techniques?
There are many reasons why data visualization techniques are important like it helps in deciphering the important information hidden in the data. It can easily unfold the details of complex data thus making it easier to understand.
Additionally, data visualization techniques can help identify data patterns and trends. This can be useful for predicting future events or understanding the relationships between different variables. It also assists in better communication of information. This is because they can make data more visually appealing and easier to understand.
There are many data visualization techniques, but some common ones include charts, graphs, and maps.
Why do we use data visualization?
There are many reasons why data visualization is important. Some of the important ones have been highlighted below:
While highlighting data in a graphical form, it is easier to see patterns and trends. This can help us make better decisions and understand the implications of our decisions.
Visual representation of data makes it more comprehensible. This is important in fields such as business, where data forms the core of making decisions like investment, marketing, and strategy decisions.
Data visualization can also help us to find new insights in total. It makes it easier to comprehend the information in a glimpse. This can lead to discoveries and a better understanding of the data.
Why data visualization is so important?
Data visualization assists in a better understanding of the data. Graphically representing hence, data makes it easier to understand patterns that may otherwise skip our eyes.
What are the types of data visualization?
There are several types of data visualization, including:
- Bar charts
- Line graphs
- Scatter plots
- Pie charts
Is Microsoft Excel a data visualization tool?
Microsoft Excel isn’t visualization software. However, is a power to assess and illustrate datasets.
What should I look for in a data visualization tool?
A data visualization tool should have a range of features that allow you to manipulate and present data effectively and efficiently. Some of the key features to look for include:
- The user can load data from a variety of sources
- It allows the user to manipulate data to create custom visualizations
- One can share the visualizations with others
- Ease of sharing visualizations for use in other applications
- Customization features that allow the user to meet your specific needs
- The ability to interact with visualizations to gain deeper insights into the data
- One can create dynamic and interactive visualizations
- Easily integrate visualizations into other applications
What are some tips for creating effective data visualizations?
There are a number of different factors to consider when creating data visualizations. Some general tips to keep in mind include:
- Consider the purpose of the visualization. What do you want to communicate with the visualization?
- Consider the audience of the visualization. How much detail do they need? What do they need to know?
- Choose the appropriate type of visualization. There are various types of visualizations, each with its strengths and weaknesses.
- Consider the data. What does it tell you? What are the important trends and patterns?
- Keep it simple. Don’t try to cram too much information into one visualization.
- Make sure the visualization is accurate. Check the data and the visualization for errors.
- Test the visualization. Show it to others and get feedback. Make sure it communicates what you want it to communicate.
What are Data Visualization Tools in Python?
While Python is a versatile programming language, it also has libraries that are used for data visualization. Eg. Matplotlib and Seaborn have inbuilt modules for plotting different graphs. Matplotlib is used to embed graphs into applications, Seaborn is used for statistical graphs
Wrapping it up !!!
The purpose of data visualization is to communicate information effectively through graphical means or pictorial representation. It is one of the key components of data science and finds wider usability by data analysts and scientists to gain insights into their data. Some common types of data visualizations include line graphs, bar charts, scatter plots, and heat maps.
Data visualization is an important tool for data science because it allows data analysts and scientists to quickly and easily gain insights into their data. It also allows them to communicate their findings to others clearly and effectively. So, if you are keen to become a data scientist and are exploring the best big data applications, excelling in using the top data visualization tools is paramount.