Sat. Feb 24th, 2024
8 Top-Notch AI Technology for Data Visualization Tools

To propel your company forward, you must be able to make educated judgments. These judgments should be based on accurate analysis of large or complicated information. It might seem like searching through a haystack for a needle. This is because it is time-consuming.

These days, AI is supercharging Data Visualization Tools. You can use AI data visualization tools to create charts, reports, and dashboards. They reveal patterns you never knew existed. Afterwards, you may incorporate these findings into your long-term plans. Enhancing process efficiency and productivity gains.

We’ve compiled a list of the ten best AI data visualization tools. This will help you make better data-driven decisions using artificial intelligence.

Top AI Data Visualization Tools You Need to Lookout:

Tableau:

Tableau is an advanced analytics and business intelligence platform driven by artificial intelligence. It helps you make better decisions faster by improving your understanding of your data.

You can use Tableau’s visualization features without coding. That’s why the program is so popular. You can use plain English to tell Tableau what you want and get tailored insights from your data. You can do this with Tableau’s natural language query capability.

Polymer:

The platform is perfect for sales, marketing, and e-commerce teams. It combines powerful AI capabilities with user-friendliness.

To begin working with Polymer, choose a connection or upload a dataset. The next step is to analyze the data using Polymer’s AI. The software is designed to produce dashboards and provide in-depth insights automatically. Put your visualizations on display in presentations. Share the links with the right people on your team. Or integrate them into your website.

Sisense:

It is a platform that facilitates Data Visualization Tools with its dynamic interface. And drag-and-drop architecture.

To make complicated data more digestible. Sisense enables the creation of interactive business information dashboards. Innovative charting and computation tools let you deal with any data set and show it as you want.

MonkeyLearn:

The tool has pre-trained classifiers and extractors to facilitate data sorting and organization. Do you dislike their use? No difficulty—make your own (entirely without coding) and customize whatever you like.

Using the tool is a breeze. The first step is to link your text data (via file uploads or app connections). To finish tagging your text, you may use pre-trained models or create your own. After the analysis, you can create visualizations. You can also integrate many data sources, such as custom fields and dates.

Power BI:

It is developed by Microsoft, and has tools that may make you an expert data visualizer. It allows you to find hidden patterns and put your data to use.

Chat is its most impressive AI function. It provides fast and accurate answers to inquiries about your data. Without writing a word of code, you may get the answers you need with this solution. Built on GPT-4’s huge language model.

Akkio:

Akkio AI may generate customized dashboards and reports according to your objectives. Akkio will immediately produce reports based on the supplied information. All you have to do is connect your data and explain the project, application, or issue.

Facebook’s HiPlot:

Discover previously unseen trends and patterns with the aid of Facebook’s HiPlot, an open-source AI data visualization. Parallel plots, a kind of data visualization well-suited to comparing and evaluating variables and datasets with many dimensions, are used to do this.

You may alter the styles of the interactive parallel plots that HiPlot employs to display data. Make your graphics stand out by plotting over several axes, adjusting color parameters, and setting custom value ranges.

Graphy:

Are you looking for an easy-to-use charting program? You can see your data via graphs on Graphy for free, even without joining up—it’s the best option.

There is no easier way to use the platform. Graphy will automatically create visualizations based on the data you put into the table on the right. There are six different kinds of charts to choose from: bar, line, combination, pie, funnel, and heatmap. Graphy’s AI writer can find outliers, summarize data, and write reports and presentations.

Last Thoughts:

Machine learning-enhanced data visualization approaches. This may provide several advantages, whether or not AI drives them. With their assistance, you may discover previously unseen trends in your data analytics. And use them to your benefit in many areas of your organization.

What is the Importance of Artificial Intelligence in Data Visualization?

Artificial Intelligence is pivotal in automating tasks and optimizing data visualization processes. AI maximizes efficiency. It customizes visualizations to user preferences. It can even predict future trends based on analysis of collected data.

How can AI-driven data visualization tools benefit users with limited analytics knowledge?

AI tools such as Google Data Studio Auto-Visualization make data visualization accessible to users of varying experiences. By suggesting suitable chart types and styles, these AI tools make the process effortless without the need for extensive knowledge of data visualization techniques.

Can you provide real-world examples of Predictive Analytics and Augmented Intelligence implemented through data visualization tools like Looker or Qlik Sense?

Looker Predictive Analytics allows businesses to forecast future trends based on historical data, aiding decision-making regarding sales, market shifts, and more. Qlik Sense Augmented Intelligence offers real-time insights during data exploration for quick and accurate decision-making in various scenarios.

How does IBM Cognos Analytics’ Explainable AI aid in creating better data visualizations?

Explainable AI in IBM Cognos Analytics ensures transparency in decision-making related to visualizations. It generates insightful visualizations and explains the significance of patterns or trends to foster an understanding of data while building trust within an analytical process.

By Alex Reed

Alex Reed, a prominent AI writer and thought leader, holds a degree in computer science and a Master's in AI and Machine Learning. Committed to simplifying complex AI concepts, she advocates for ethical AI development. Alex's research explores both AI possibilities and ethical considerations, playing a vital role as a writer, mentor, and educator in the rapidly evolving field of artificial intelligence.

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