4 minutes

The Best 10 AI Tools to Analyze Data in 2023

There are multiple tools to visualize, analyze, and keep track of your data, allowing you to get the insights you need to achieve your goals. But, with so many tools to choose from, how do you know which one is the right for you? Let's find out.

Data analysis is more important than ever. And, if you’re not a professional data analyst (and maybe even if you are), you need the right AI tools to analyze data.

There are multiple tools to visualize, analyze, and keep track of your data, allowing you to get the insights you need to achieve your goals. But, with so many tools to choose from, how do you know which one is the right for you?

What can AI tools do for you and your data exactly?

Let’s dive in.

How Is AI Used in Analytics?

With AI becoming more and more advanced every day, AI is becoming a more powerful, efficient, and approachable solution to process data.

Some of the modern ways of using AI in Analytics are:

  • Finding insights: AI can examine vast amounts of data and find the trends and patterns needed to help users find the insights needed to improve their sales and marketing efforts, customer interactions, engagement, and more.
  • Streamline data analysis: By funneling all data into one solution, users can gain a more complete overview of their data, and make it easy to understand and keep track of.
  • Predict outcomes: With Predictive AI, users can develop forecasts and analyze potential scenarios to determine the one with the better chances of success.

What’s more, practically no other alternative can be used to solve all the issues AI does, or to analyze data in a more efficient and insightful way.

The Relationship Between AI and Data Analysis

The advent of artificial intelligence (AI) has revolutionized the way we approach data analysis. Traditional methods of data analysis required manual effort and time to derive insights from vast datasets. With AI data analysis, this process is expedited, allowing for real-time insights and predictive capabilities. AI algorithms can sift through massive amounts of data, identifying patterns, anomalies, and trends that might go unnoticed by human analysts.

Moreover, data analysis AI tools bring a level of consistency and accuracy that's hard to achieve manually. By leveraging machine learning and deep learning models, AI data analytics can adapt and learn from new data, continuously refining its analysis methods and ensuring up-to-date insights.

The Future of Data Analysis: Entwined with AI

As we venture further into the digital age, the symbiotic relationship between AI and data analysis will only deepen. The future of ai data analytics is not just about faster computations but about smarter and more intuitive analytics.

Predictive analytics, sentiment analysis, and real-time data processing are just the tip of the iceberg. In the near future, we can expect AI-driven tools to become even more sophisticated, offering capabilities like emotion detection, real-time anomaly detection, and even prescriptive analytics that can suggest actions based on the data analysis.

Moreover, as businesses and organizations generate more data, the demand for AI-enhanced data analysis tools will surge. Integrating AI into data analysis workflows will soon become the norm rather than the exception.

In conclusion, as AI continues to evolve and integrate deeper into the realm of data analysis, businesses and individuals must adapt and harness these powerful tools to stay ahead in an increasingly data-driven world.

Why should you use AI for your Data Analysis?

So, you already have access to your website’s analytics or the data of your marketing efforts, what can AI do for you?

With AI, you can make sure you’re analyzing all data uniformly. Since AI lacks human bias and can examine vast amounts of data at lightning-fast speed, it can predict how your campaigns will go, and even proactively offer insights to ensure you’re catching all info.

This allows you to examine and keep track of your data even if you’re not a data scientist. After all, with AI products, you can skip the long and expensive process of developing algorithms, and skip right to analyzing your data.

The best 10 AI tools to analyze data

Here are some of the best AI tools to analyze data:

1. Polymer 

Polymer Search is a robust tool with a powerful AI made to turn your boring data into a more streamlined, powerful, and flexible database. All without writing a single line of code.

Polymer powers your spreadsheet with a robust AI, to help you analyze your data and improve your understanding of it, all with a few clicks. There’s no long onboarding process or training videos to go through. Simply upload your spreadsheet to Polymer and instantly transform it into a streamlined database easy to explore.

Simply sign in to your free Polymer account, and upload your spreadsheet or share it from the cloud. Polymer Search will then use its AI to encrypt and analyze your data, transforming it into a powerful web app that’s easy to analyze and search through.

You can further customize the web app with multiple layouts at any time, getting the one that better fits your current needs. You can also use the “Smart Pivot” tool to use as a powerful and improved pivot table.

Polymer is the simplest way of using AI to analyze your data, while offering you intuitive visualization capabilities and almost limitless ways of interacting with your data.

Drop your first spreadsheet and try it yourself.

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2. Tableau

Tableau is an analytics and data visualization platform that allows users to interact with the data they have without the need for coding.

The platform is easy to use, allowing users to create and modify dashboards and reports in real-time, and seamlessly share them across users and teams. It comes with all the features expected from tools like these, supporting databases of all sizes and offering multiple visualization options for users to analyze their data.

Tableau also allows users to run the platform both in the cloud or on-premise for users looking for a more hermetic environment for their data.

3. MonkeyLearn

MonkeyLearn is another no-coding platform with AI data analysis features for users to visualize and rearrange their data.

The platform comes with multiple AI-powered text analysis tools to instantly analyze and visualize data to the user’s needs. Users can set up text classifiers and text extractors to automatically sort data according to the right topic or intent, and extract product features or user data.

The tool comes with multiple integrations to work with whichever tools are already being used, and a simple and intuitive UI matching the simplicity of the platform.

4. Microsoft Power BI 

Microsoft Power BI is a famous business intelligence platform that also gives users the ability to sort through their data and visualize it to search for insight.

The platform allows users to import data from practically anywhere, and get started on creating reports and dashboards as they need. Users can also build machine learning models and access other AI-powered features to help them analize their data.

The platform comes with multiple integrations, including a native Excel integration, and a UI faster and more responsive than some other solutions, although often at a higher price tag.

5. Sisense 

Sisense is another data analytics platform that allows both analysts and developers to sort through and visualize their data.

The platform is easy to use, with multiple drag-and-drop tools and a responsive UI made to streamline the experience. Sisense also allows users to access their “In-Chip” technology and choose between RAM and CPU to process the data, making computation faster when handling large datasets.

Although the platform has limited visualization capabilities, it’s a good option for users with basic visualization and reporting needs looking to handle smaller datasets.

6. Microsoft Excel

Microsoft Excel was the best data analysis tool when it was created, and remains a competitive one today.

With Excel’s Data Analysis Toolpak, users can analyze and process their data, create multiple basic visualizations, and quickly filter through data with the help of search boxes and pivot tables. Excel also allows users to create machine learning models with no coding, use formulas to calculate data from clusters, and even create complex neural networks.

Although Excel’s capabilities have kept up with the times, it remains limited by its spreadsheet model and high learning curve, even without the need to code.

7. Akkio

Akkio is a business analytics and forecasting tool for users to analyze their data and predict potential outcomes.

This no-coding platform comes with lead scoring features made for users to qualify and segment their lead lists and prioritize hot leads. The forecasting features allow users to use the data they have to get future predictions on practically any dataset. 

The tool is fast and intuitive, and comes with few but useful integrations to get data to and from other tools.

8. Qlik

QlikView is another business intelligence and data visualization solution that allows users to tap into AI technology to analyze their data.

The platform comes with multiple data exploration features and a versatile platform that’s friendly to both technical and non-technical users. Teams can seamlessly collaborate on the platform using simple drag-and-drop editors and workflows to manipulate their data to their liking.

Although the platform is highly functional, the high cost and comparatively low AI feature set make QlikView a better choice only for users who can use the full extent of the platform.

9. Looker

Part of the Google Cloud, Looker is another no-code data analysis and business intelligence tool with powerful capabilities and multiple integrations.

Looker is capable of processing large databases, allowing users to make multiple dashboards and reports, and condensing all their data sources into one. The platform is also capable of advanced data modeling features and comes with the benefit of being backed by Google.

Although the platform is easy to navigate, it doesn’t provide a lot of flexibility, and building reports from scratch can be time-consuming.

10. SAP BusinessObjects

SAP BusinessObjects allows less-technical users to analyze, visualize, and report on their data, all while seamlessly integrating to the rest of the SAP suite.

With it, users can access AI and machine learning technology, and use them for data modeling and visualization, enhanced reporting, and dashboarding. The tool also allows users to access predictive forecasting features to gain deeper insight into their data.

However, although the platform has lowered its pricing, the cost of the solution, particularly when getting platform licenses, can still be prohibitive. That’s why this tool is better for users who are already SAP customers and can benefit from an AI data tool that works along with the other SAP tools they’re already using.

Final Thoughts

AI tools can help you analyze data deeper than ever before. You can use them to get the insights you’re looking for, find trends and patterns, and make better data-driven decisions. With AI being more affordable and accessible to users, it’s better to adopt it sooner rather than later.

Get started today by dropping your first spreadsheet into Polymer, and see how easy it is to analyze your data with the help of Polymer’s powerful AI.

Posted on
August 9, 2023
under Blog
August 9, 2023
Written by
Rand Owens
Founding team member at Motive (Formerly KeepTruckin) and passionate about all things Marketing, RevOps, and Go-To-Market. VP of Marketing @ Polymer Search.

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