Widely Used Data Visualization tools

Widely Used Data Visualization tools

1. Tableau
2. Microsoft Power BI
3. QlikView
4. D3.js (JavaScript library)
5. Highcharts (JavaScript library)
6. matplotlib (Python library)
7. ggplot2 (R library)
8. Plotly (Python and JavaScript library)
9. Leaflet (JavaScript library for interactive maps)
10. Infogram (cloud-based tool for creating infographics and charts)

Tableau

Tableau is a data visualization and business intelligence software that helps people see and understand their data. It allows users to connect to various data sources, such as spreadsheets, databases, and cloud-based services, and then create interactive visualizations and dashboards with the data. These visualizations can be shared with others, embedded in websites, and even published to the web for anyone to access. Tableau also offers a wide range of data analysis and data blending capabilities. It's widely used in many organizations to explore, analyze and visualize their data to make better decisions.

Pros of Tableau:

Intuitive and user-friendly interface: Tableau's drag-and-drop interface makes it easy for users to create visualizations and dashboards, even with little to no programming experience.

Wide range of data connectors: Tableau can connect to a variety of data sources, including spreadsheets, databases, and cloud-based services.

Advanced analytics and data blending capabilities: Tableau offers a wide range of data analysis and data blending capabilities, making it a powerful tool for data exploration and discovery.

Interactive visualizations: Tableau's visualizations are highly interactive, allowing users to explore and analyze data in new ways.

Scalability: Tableau can handle large amounts of data and can be scaled to meet the needs of organizations of any size.

Cons of Tableau:

Cost: Tableau can be relatively expensive, especially for organizations that need multiple licenses or advanced features.

Limited customization options: While Tableau offers a wide range of built-in visualizations, advanced users may find the customization options to be limited.

Limited data preparation capabilities: Tableau does not provide advanced data preparation capabilities. Users may need to clean, transform and enrich the data before using it in Tableau.

Learning curve: While Tableau's interface is user-friendly, it may take some time to learn how to use the tool's advanced features.

Limited integration with other tools: Tableau may not integrate well with other tools in an organization's data stack.

Microsoft Power BI

Microsoft Power BI is a business intelligence and data visualization tool developed by Microsoft. It allows users to connect to various data sources, such as spreadsheets, databases, and cloud-based services, and then create interactive visualizations and dashboards with the data. Power BI also offers advanced analytics and data modeling capabilities, as well as the ability to create reports and share them with others. Power BI can be used both as a stand-alone tool or integrated with other Microsoft products such as Excel and SharePoint.

Pros of Power BI:

1. Intuitive and user-friendly interface: Power BI's drag-and-drop interface makes it easy for users to create visualizations and dashboards, even with little to no programming experience.
2. Advanced analytics and data modeling capabilities: Power BI offers a wide range of data analysis and data modeling capabilities, making it a powerful tool for data exploration and discovery.
3. Integration with other Microsoft products: Power BI can be integrated with other Microsoft products such as Excel and SharePoint, making it easy to share data and collaborate with others.
4. Cost: Power BI is a relatively affordable option compared to other business intelligence and data visualization tools.

Cons of Power BI:

1. Limited data connectors: Power BI can connect to a limited number of data sources compared to other business intelligence and data visualization tools.
2. Limited customization options: While Power BI offers a wide range of built-in visualizations, advanced users may find the customization options to be limited.
3. Limited data preparation capabilities: Power BI does not provide advanced data preparation capabilities. Users may need to clean, transform and enrich the data before using it in Power BI.
4. Limited scalability: Power BI may not handle large amounts of data as well as some other business intelligence and data visualization tools.
5. Limited support for real-time data: Power BI is not a real-time data visualization tool, it has a delay of few minutes to hours depending on the data source and complexity of the data.

QlikView

QlikView is a business intelligence and data visualization tool developed by Qlik. It uses a unique associative data model that allows users to easily explore and analyze large sets of data. QlikView allows users to connect to various data sources, such as spreadsheets, databases, and cloud-based services, and then create interactive visualizations and dashboards with the data. It also offers advanced analytics and data modeling capabilities, as well as the ability to create reports and share them with others.

Pros of QlikView:

1. Unique associative data model: QlikView's associative data model allows users to easily explore and analyze large sets of data, making it a powerful tool for data discovery.
2. Intuitive and user-friendly interface: QlikView's drag-and-drop interface makes it easy for users to create visualizations and dashboards, even with little to no programming experience.
3. Advanced analytics and data modeling capabilities: QlikView offers a wide range of data analysis and data modeling capabilities, making it a powerful tool for data exploration and discovery.
4. Scalability: QlikView can handle large amounts of data and can be scaled to meet the needs of organizations of any size.
5. Mobile access: QlikView allows users to access and interact with visualizations and dashboards from mobile devices.

Cons of QlikView:

1. Cost: QlikView can be relatively expensive, especially for organizations that need multiple licenses or advanced features.
2. Limited customization options: While QlikView offers a wide range of built-in visualizations, advanced users may find the customization options to be limited.
3. Limited data preparation capabilities: QlikView does not provide advanced data preparation capabilities. Users may need to clean, transform and enrich the data before using it in QlikView.
4. Learning curve: While QlikView's interface is user-friendly, it may take some time to learn how to use the tool's advanced features.
5. Limited integration with other tools: QlikView may not integrate well with other tools in an organization's data stack.

D3.js (Data-Driven Documents)

D3.js (Data-Driven Documents) is a JavaScript library for creating interactive data visualizations in web browsers. It allows developers to bind data to the Document Object Model (DOM), and then apply data-driven transformations to the document, such as changing the position, size, and color of elements. D3.js provides a wide range of built-in visualization types, such as bar charts, line charts, scatter plots, and maps, and it also allows developers to create custom visualizations.

Pros of D3.js:

1. Customizability: D3.js allows developers to create custom data visualizations, providing a high degree of control over the design and functionality of the visualization.
2. Wide range of built-in visualization types: D3.js provides a wide range of built-in visualization types, such as bar charts, line charts, scatter plots, and maps.
3. Dynamic visualizations: D3.js allows developers to create dynamic visualizations that respond to user input and update in real-time.
4. Interactivity: D3.js allows developers to create interactive visualizations, with features such as hover effects, tooltips, and click events.
5. Cross-browser compatibility: D3.js is compatible with a wide range of web browsers, including Internet Explorer, Chrome, Firefox, and Safari.

Cons of D3.js:

1. Steep learning curve: D3.js requires a solid understanding of JavaScript and web development concepts, making it a challenging library for beginners to learn.
2. Limited documentation: While there are many examples and tutorials available, the documentation for D3.js is not as extensive as it could be.
3. No built-in data connectors: D3.js does not provide built-in data connectors, so developers need to handle the data retrieval process themselves.
4. Limited built-in chart types: D3.js does not provide as many built-in chart types as some other data visualization libraries
5. Limited support for real-time data: D3.js is not a real-time data visualization library, it has a delay of few minutes to hours depending on the data source and complexity of the data.

Highcharts

Highcharts is a JavaScript library for creating interactive data visualizations in web browsers. It provides a wide range of built-in chart types, such as line charts, bar charts, pie charts, and scatter plots, as well as a simple API for creating custom visualizations. Highcharts also allows developers to create interactive visualizations, with features such as hover effects, tooltips, and click events. Additionally, it supports for exporting the chart as image in various formats, as well as printing the chart directly from the browser.

Pros of Highcharts:

1. Wide range of built-in chart types: Highcharts provides a wide range of built-in chart types, such as line charts, bar charts, pie charts, and scatter plots.
2. Easy to use: Highcharts has a simple API that makes it easy to create and customize charts.
3. Interactivity: Highcharts allows developers to create interactive visualizations, with features such as hover effects, tooltips, and click events.
4. Cross-browser compatibility: Highcharts is compatible with a wide range of web browsers, including Internet Explorer, Chrome, Firefox, and Safari.
5. Exporting and Printing: Highcharts supports exporting the chart as image in various formats, as well as printing the chart directly from the browser.

Cons of Highcharts:

1. Limited customization options: While Highcharts offers a wide range of built-in chart types, advanced users may find the customization options to be limited.
2. Limited data connectors: Highcharts does not provide built-in data connectors, so developers need to handle the data retrieval process themselves.
3. Limited support for real-time data: Highcharts is not a real-time data visualization library, it has a delay of few minutes to hours depending on the data source and complexity of the data.
4. Limited support for 3D visualizations: Highcharts does not provide built-in support for 3D visualizations, which could be a limitation for some use cases.
5. Cost: Highcharts is a commercial library and requires a license for usage in production environments.

matplotlib

matplotlib is a plotting library for the Python programming language. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK. It provides a wide range of built-in chart types, such as line plots, scatter plots, bar plots, histograms, and more. It also allows for customization of the plots through the use of various parameters, and also supports exporting the plots as image in various formats.

Pros of matplotlib:

1. Wide range of built-in chart types: matplotlib provides a wide range of built-in chart types, such as line plots, scatter plots, bar plots, histograms, and more.
2. Customizability: matplotlib allows for customization of the plots through the use of various parameters, such as axis labels, plot title, gridlines, etc.
3. Exporting options: matplotlib supports exporting the plots as image in various formats, such as PNG, PDF, SVG, etc.
4. Integration with other Python libraries: matplotlib can be integrated with other Python libraries such as NumPy, SciPy, and pandas for data analysis and manipulation
5. Active Community: matplotlib has a large active community that provides support and develops new features.

Cons of matplotlib:

1. Limited interactivity: matplotlib does not provide built-in support for interactivity, such as hover effects, tooltips, and click events.
2. Limited support for real-time data: matplotlib is not a real-time data visualization library, it has a delay of few minutes to hours depending on the data source and complexity of the data.
3. Steep learning curve: matplotlib's API can be complex and may require some time to fully understand.
4. Limited support for 3D visualizations: matplotlib does not provide built-in support for 3D visualizations, which could be a limitation for some use cases.
5. Limited support for web-based visualizations: matplotlib is primarily designed for creating visualizations in desktop applications, and its support for web-based visualizations is limited.

ggplot2

ggplot2 is a data visualization package for the R programming language. It is built on the grammar of graphics, which is a way of creating plots by specifying the components of the plot, such as the data, aesthetics, and geometries. ggplot2 provides a wide range of built-in chart types, such as line plots, scatter plots, bar plots, histograms, and more. It also allows for customization of the plots through the use of various parameters, and also supports exporting the plots as image in various formats.

Pros of ggplot2:

1. Customizability: ggplot2 allows for customization of the plots through the use of various parameters, such as axis labels, plot title, gridlines, etc.
2. Wide range of built-in chart types: ggplot2 provides a wide range of built-in chart types, such as line plots, scatter plots, bar plots, histograms, and more.
3. Exporting options: ggplot2 supports exporting the plots as image in various formats, such as PNG, PDF, SVG, etc.
4. Integration with other R libraries: ggplot2 can be integrated with other R libraries such as dplyr, tidyr, and lubridate for data analysis and manipulation
5. Grammar of Graphics: ggplot2 is built on the grammar of graphics, which provides a consistent and efficient way of creating plots.

Cons of ggplot2:

Limited interactivity: ggplot2 does not provide built-in support for interactivity, such as hover effects, tooltips, and click events.

Limited support for real-time data: ggplot2 is not a real-time data visualization library, it has a delay of few minutes to hours depending on the data source and complexity of the data.

Steep learning curve: ggplot2's API can be complex and may require some time to fully understand.

Limited support for 3D visualizations: ggplot2 does not provide built-in support for 3D visualizations, which could be a limitation for some use cases.

Limited support for web-based visualizations: ggplot2 is primarily designed for creating visualizations in desktop applications, and its support for web-based visualizations is limited.

Plotly

Plotly is a Python and JavaScript library for creating interactive data visualizations in web browsers. It provides a wide range of built-in chart types, such as line charts, bar charts, scatter plots, and maps, as well as the ability to create custom visualizations. Plotly also allows developers to create interactive visualizations, with features such as hover effects, tooltips, and click events. Additionally, Plotly allows for creating and sharing interactive dashboards and has built-in support for real-time streaming data.

Pros of Plotly:

1. Customizability: Plotly allows developers to create custom data visualizations, providing a high degree of control over the design and functionality of the visualization.
2. Wide range of built-in chart types: Plotly provides a wide range of built-in chart types, such as line charts, bar charts, scatter plots, and maps.
3. Interactivity: Plotly allows developers to create interactive visualizations, with features such as hover effects, tooltips, and click events.
4. Cross-browser compatibility: Plotly is compatible with a wide range of web browsers, including Internet Explorer, Chrome, Firefox, and Safari.
5. Real-time streaming data: Plotly has built-in support for real-time streaming data and allows for creating and sharing interactive dashboards.

Cons of Plotly:

Limited data connectors: Plotly does not provide built-in data connectors, so developers need to handle the data retrieval process themselves.

Limited support for 3D visualizations: Plotly does not provide built-in support for 3D visualizations, which could be a limitation for some use cases.

Cost: Plotly is a commercial library and requires a license for usage in production environments.

Steep learning curve: Plotly's API can be complex and may require some time to fully understand.

Limited documentation: While there are many examples and tutorials available, the documentation for Plotly is not as extensive as it could be.

Leaflet

Leaflet is a JavaScript library for creating interactive maps for the web. It allows developers to create maps, add layers, and customize the appearance of maps using a simple API. Leaflet is lightweight and easy to use, making it a popular choice for creating maps on the web. It also supports a wide range of base maps and tile layers, and allows for easy integration with other JavaScript libraries and frameworks.

Pros of Leaflet:

1. Lightweight and easy to use: Leaflet has a simple API that makes it easy to create and customize maps.
2. Wide range of base maps and tile layers: Leaflet supports a wide range of base maps and tile layers, including OpenStreetMap, Mapbox, and Bing Maps.
3. Customization options: Leaflet allows for customization of the maps through the use of various parameters, such as zoom levels, map controls, and markers.
4. Cross-browser compatibility: Leaflet is compatible with a wide range of web browsers, including Internet Explorer, Chrome, Firefox, and Safari.
5. Integration with other libraries: Leaflet can be easily integrated with other JavaScript libraries and frameworks, such as AngularJS, React, and Vue.

Cons of Leaflet:

1. Limited support for 3D visualizations: Leaflet is primarily a 2D mapping library, and it does not provide built-in support for 3D visualizations, which could be a limitation for some use cases.
2. Limited data connectors: Leaflet does not provide built-in data connectors, so developers need to handle the data retrieval process themselves.
3. Limited support

Infogram

Infogram is an online data visualization and infographics creation tool. It allows users to create interactive charts, maps, and infographics using a drag-and-drop interface. It also offers a wide range of pre-designed templates and themes to choose from, making it easy for users to create professional-looking visualizations even with little to no design experience. Infogram also allows for easy sharing and collaboration, with the ability to publish visualizations to the web and share them with others.

Pros of Infogram:

1. User-friendly interface: Infogram's drag-and-drop interface makes it easy for users to create visualizations, even with little to no design experience.
2. Wide range of pre-designed templates and themes: Infogram offers a wide range of pre-designed templates and themes to choose from, making it easy for users to create professional-looking visualizations.
3. Collaboration and sharing: Infogram allows for easy sharing and collaboration, with the ability to publish visualizations to the web and share them with others.
4. Integration with other platforms: Infogram can be integrated with other platforms such as WordPress, Squarespace, and Google Drive.
5. Cost: Infogram is a relatively affordable option compared to other data visualization tools.

Cons of Infogram:

1. Limited customization options: While Infogram offers a wide range of built-in visualizations, advanced users may find the customization options to be limited.
2. Limited support for real-time data: Infogram is not a real-time data visualization tool and has a delay of few minutes to hours depending on the data source and complexity of the data.
3. Cost: While Infogram offers a free plan, advanced features and more data usage may require upgrading to