Must Try AI Tools for Data Visualization in 2024
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Data visualization represents data in the form of graphs and charts. The data scattered across the internet is raw, unstructured, and complex. For businesses, it’s essential to understand the raw information to draw valuable insights. These insights help in understanding the audience and potential customers. Therefore, to gain such insights from complex data, presenting them as charts and graphs is useful. Such visualization helps in making informed and better decisions. With the advances in technology and AI, it’s easier to use data visualization methods. There are tons of AI tools for data visualization that will make the process seamless. You can use such tools to improve your workflow and learn more. These tools help businesses, researchers, science, and many fields driven by data.
What are AI Data Visualization Tools?
Data visualization is a technique or methodology used to represent raw data in a visually appealing and understandable form. Now, with AI, data visualization has transformed to higher scales. AI Data Visualization tools are software or applications that use AI to improve the visualization process. Using AI tools for data visualization can automate the process of creating and interpreting visual representations of data.
Top AI Tools For Data Visualization
Tableau AI is like an intelligent assistant for data experts, making their work easier. It helps them understand data and create excellent visuals faster. With features like Einstein Copilot, it guides them through tasks and boost the quality of graphs and dashboards. It keeps everything safe and fair with its Einstein Trust Layer, ensuring all brilliant insights are secure and ethical. Tableau AI helps everyone in a business by giving personalized insights. It’s like a customized data butler serving the correct information at the right time. With tools like Data Stories and Einstein Discovery, it’s easier to explain data, explore ideas, and get intelligent suggestions.
Key Features
- Einstein Copilot: Assists users through tasks and enhances the quality of visualizations and dashboards.
- Einstein Trust Layer: Ensures all AI-generated insights are both secure and ethical.
- Personalized Insights: Empowers all users within a business with intelligent and tailored insights.
- Data Stories: Enables the creation of automated, easy-to-understand explanations alongside visualizations, enhancing comprehension of insights.
- Explain Data & Einstein Discovery: These capabilities offer plain-language explanations and trustworthy predictions.
Pros
- Enhances productivity by reducing repetitive tasks.
- Automates data analysis, preparation, and governance.
- Provides contextual guidance for improved visualization.
- Ensures secure and ethical AI-powered insights.
- Empowers users with personalized insights seamlessly.
Cons
- Requires adaptation time to AI-driven functionalities.
- Effectiveness depends on accurate and quality data.
Pricing
Tableau offers three pricing models:
- Tableau Creator: $75/month per user
- Tableau Explorer: $42/month per user
- Tableau Viewer: $15/month per user
Microsoft’s Power BI is an efficient data visualization tool. It allows you to turn your data into interactive visuals using advanced data analysis tools. It also has AI capabilities and a user-friendly report-creation tool. You can create datasets from any source and add them to the OneLake data hub to develop a source of truth for your data. Power BI makes it easy to embed and share reports in other Microsoft services such as Teams, PowerPoint, Excel, and Power Platform. Using AI-powered insights, you can quickly find patterns in data, create reports instantly, and get answers to your queries. One of the most useful features of Power BI is the Copilot. It helps create reports quickly by describing what you want or asking questions about your data. You can add insightful text summaries to help you understand your data and tailor your narratives’ tone, scope, and style. Additionally, you can create DAX calculations faster by asking Copilot in Power BI to suggest relevant code and entire functions.
Key Features
- Data Visualization: Allows efficient data visualization using robust data analysis tools
- AI-driven Insights: Integrated AI-powered insights to identify patterns, generate instant reports, and answer queries instantly
- Report Creation: Offers user-friendly tool for creating reports
- Data Integration: Enables the creation of datasets from various sources
- AI Copilot: Aids in creating reports by interpreting descriptions. It also answers questions related to data.
Pros
- Advanced data visualization capabilities
- Integration of AI-powered insights
- User-friendly creation of report
- Seamless embedding and sharing
Cons
- Beginners might need help navigating the tool’s functionality.
Pricing
Microsoft’s Power BI offers three pricing models.
- Power BI Pro: $10.00 user/month
- Power BI Premium Per User: $20.00 user/month
Sisense’s Fusion Analytics Platform is a robust data visualization tool. Using this tool, businesses can make smarter decisions and engage customers efficiently. It uses smart AI-based analytics for advanced insights from various data sources. It offers two integration methods. One is an easy-to-use application for non-coders. The second one is a more flexible approach with SDKs and APIs for developers. You can integrate analytics into the interface and development workflow. This allows users to see enhanced analytics using charts and graphs. You can ask questions in plain language and receive AI-generated answers.
Furthermore, the tool allows users to add customized analytics to their apps using its Sisense Fusion Embed feature. This way, it’s easier to understand insights, helping make better decisions backed by data. Developers can include analytics in the code using Sisense Compose SDK. It allows the creation of purpose-built analytics parts that work with existing tech and tools.This is a cloud-based platform that offers easy maintenance.
It works well in different cloud environments and can adapt to different scales. You can create analytics without code or with low code and share insights using different visual tools. Lastly, Sisense is highly customizable. You can control the app’s look and feel using APIs and SDKs. It also allows the connection of other apps using special frameworks, adding dynamic content to the product.
Key Features
- Data Analytics: Allows extraction of valuable insights from different data sources
- Data Visualization: It offers effective data visualization through charts and graphs. This makes more data accessible and understandable.
- Cloud-Based Platform: Offers cloud-based accessibility, ensuring easy maintenance.
- No/Low Code Analytics: Allows the creation of analytics without extensive coding. This enables users to share insights using various visual tools.
Pros
- Utilizes AI-driven analytics for enhanced insights.
- The platform provides integration options for both non-coders and developers.
- It provides clear and enhanced data representation
- The platform is highly customizable providing flexibility
Cons
- It requires more data information to use advanced features.
- Some technical knowledge is needed to use customization features.
Pricing
Contact for pricing
Datawrapper is a tool that allows you to create charts, maps, and tables. It offers 19 interactive and responsive chart types ranging from simple bars and lines to arrow, range, and scatter plots. The tool also provides three interactive and responsive map types to create anything from locator maps to thematic choropleth and symbol maps. Its responsive data tables allow for lots of styling options and let you include a bar, column & line charts, heatmaps, images, a search bar, and pagination. You can copy your data from the web, Excel, or Google Sheets. You can also upload CSV/XLS files or link to a URL or Google Sheet for live-updating charts. It allows you to copy the responsive embed code into your CMS or website to show the interactive chart or export it as a PNG, SVG, or PDF for printing.
Key Features
- Chart Types: Offers 19 interactive chart types, from bars and lines to scatter and range plots.
- Map Visualization:Provides three interactive map types, including choropleth and symbol maps.
- Responsive Data Tables:Allows extensive styling options and includes charts, images, and search options.
- Data Input Options:Enables data input via web copy, Excel, Google Sheets, CSV/XLS file upload, or URL linking.
- Embedding and Exporting: Allows responsive embedding into CMS or websites and export options in PNG, SVG, or PDF formats.
Pros
- Offers a wide variety of chart types and maps.
- Provides diverse styling options for data tables.
- Offers multiple data input sources.
Cons
- Limited customization for advanced users
- Certain features may require a paid subscription.
Pricing
Datawrapper offers three pricing models
- Free: Basic features at no cost
- Custom: $599/month or $5990 per year
- Enterprise: Contact for custom pricing
HiPlot by Facebook is a visualization tool designed especially for AI researchers who work with complex, high-dimensional data. Its primary purpose is to help researchers discover correlations and patterns within their datasets. Thus providing a better understanding of data nuances. It is also available as a Python library, which users can install easily. It supports both 2D and 3D plotting and provides a variety of plot types, including line plots, scatter plots, and surface plots. You can also use different color schemes, focus on certain ranges, and more in your charts & graphs. The tool also supports CSV or JSON file parsing and even custom Python parsers. HiPlot is user-friendly and can be integrated into IPython notebooks or servers.
Key Features
- Data Visualization: Effective data visualization features for complex and high-dimensional data.
- Python Library: It is available as a Python library, which can be easily installed using a command.
- 2D and 3D Plotting: It supports both 2D and 3D plotting for different visualization needs.
- Data Parsing: Supports CSV or JSON file parsing along with the use of custom Python parsers.
Pros
- Suited for dealing with complex and high-dimensional data
- Offers various plot types.
- Enables easy customization of visualizations.
- Allows for extendability and parsing support.
Cons
- It may have limited capabilities for extremely large datasets.
Pricing
Hiplot is free to use
Google’s Looker Studio is a powerful tool for visualizing and reporting data. It enables users to create interactive dashboards and reports with their data and is part of the Google Workspace suite of tools. It works seamlessly with other Google products like Google Sheets, BigQuery, and Google Analytics. With Data Studio, users can easily connect to their data sources, create custom charts and tables, and share their dashboards using a secure web link. Additionally, it offers pre-built templates and connectors to popular data sources. Thus making it easy to create data visualizations.
Key Features
- Data Visualization:Enables the creation of interactive and customizable dashboards for data visualization.
- Integration with Google Workspace:It allows integration with Google’s suite of tools like Google Sheets and Google Analytics.
- Data connection: Allows easy connection to data sources and custom charts and tables creation.
- Customization: Offers pre-built templates and connectors for various data sources.
Pros
- Seamless integration with Google Workspace.
- User-friendly interface for data visualization.
- Offers pre-built templates and connectors for various data sources.
Cons
- Limited advanced analytics features compared to some other specialized tools.
- The steeper learning curve for more complex data analysis requirements.
Pricing
- Looker Studio: No charge
- Looker Studio Pro: $9 per user per project per month
Qlik Sense is a business intelligence and data visualization tool. You can connect to multiple data sources for effective data analysis. You can also create interactive dashboards and perform data analysis tasks. The tool also supports various data types. This includes structured, semi-structured, and unstructured data. It also offers advanced analytics features like data mining, predictive analysis, and storytelling. Qlik Sense’s Insight Advisor provides valuable analyses and insights. It also automates analytics creation and data preparation processes. Plus, it supports natural language interaction for flexible insights and analytics. Its AutoML feature offers key-driver analysis, predictive analytics, and what-if scenarios. The platform is user-friendly and easy to use.
Key Features
- Data Connectivity:It connects to data sources for creating interactive dashboards.
- Data Types: The tool can handle various data types, such as structured or unstructured.
- Data Analysis: It offers advanced analysis functions such as data mining and predictive analytics.
Pros
- Flexible data connectivity and support for different data types
- Advanced analytics capabilities for gaining valuable insights.
- Qlik AutoML facilitates predictive analytics and key-driver analysis within the tool.
Cons
- Requires careful data preparation for accurate and effective analysis.
- Advanced features may overwhelm casual users.
Pricing
- Standard: $20 user/month. Ten user minimum, billed annually
- Premium: $2,700/month, billed manually.
- Enterprise: Contact for custom pricing
Importance of AI in Data Visualization
Artificial Intelligence in data visualization has led to significant advancements. It makes the process easier and quick. Here are some of the highlighted aspects of why AI is important in data visualization.
- Automated Insights: AI data visualization tools are capable of generating insights from data automatically. They can identify trends, patterns, and correlations in the data.
- Enhanced Interactivity:AI-driven data visualization tools enhance interactivity. This allows users to explore and interact with data graphs and charts.
- Natural Language Processing: Some AI data visualization tools use natural language for better interaction. This helps to gain information in plain English language. You can ask questions or provide commands in plain language. The tool will then generate a response following the command.
- Predictive Analytics: Such tools can make predictions for future trends based on past data patterns.
- Complex Data Handling: These tools are capable of handling large and complex datasets. They can take large volumes of complex data and turn it into an understandable form.
Use Cases Across Industries
- Healthcare: AI-driven visualization tools aid in analyzing patient data, medical imaging, and genomic data. This helps to identify and optimize treatments.
- Finance:These tools help in risk assessment, fraud detection, market analysis, and more. They do this by visualizing complex financial data for better decision-making.
- Marketing and Sales:Data visualization can help marketers understand consumer behavior. It helps them draw patterns, insights, and performance.
- Education and Research:In education and research, such techniques help identify educational patterns and more. This way, it helps in making better decisions in the education sector.
Conclusion
Artificial intelligence in data visualization has made a great impact. It aids in deriving meaningful insights in a matter of minutes, making the process effortless. Such AI-powered tools have changed how we represent data and gain insights for good. These tools allow quicker and better decision-making, helping businesses in the process. They provide a deeper understanding of the data, allowing businesses to use their data information to the full extent. As technology is evolving, these tools will likely continue to evolve. In the future, they will provide more sophisticated features and ease of use in data visualization.