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5 Amazing AI Tools for Data Analysis [2024 Updated]

July 24, 2023

Nowadays, using AI for data analysis has become essential. However, finding a free and effective AI generator can be a challenge. If you're wondering how to write an article using an AI generator, this guide is for you.

In this article, we provide valuable insights on utilizing AI tools for data analysis, along with a spotlight on WPS Office as a powerful alternative to MS Office. Discover the possibilities of AI and unlock new levels of data analysis proficiency.

Part 1: What is AI Data Analysis

AI Data Analysis, also known as AI-powered data analytics, is the application of artificial intelligence techniques and algorithms to extract meaningful insights and patterns from large volumes of data. It combines the power of AI and data analysis to automate and enhance the process of deriving valuable information from complex datasets.

The analytical scope of AI Data Analysis is vast and encompasses various types of data analysis. Here are some key analytical areas where AI is utilized:

  1. Descriptive Analysis: Summarizing and describing data to get an overview of its main characteristics.

  2. Diagnostic Analysis: Investigating relationships between variables to understand the causes of specific patterns or trends.

  3. Predictive Analysis: Using historical data to make predictions or forecasts about future events or outcomes.

  4. Prescriptive Analysis: Providing recommendations and optimal courses of action based on data analysis.

  5. Exploratory Analysis: Exploring data to discover patterns, relationships, or hidden insights.

  6. Text Analysis: Extracting insights from unstructured textual data, such as sentiment analysis or topic modeling.

  7. Visual Analysis: Presenting data visually through charts, graphs, or interactive dashboards to understand patterns and communicate insights.

Part 2: How to Use AI for Data Analytics – Excel Labs

Excel Labs is a powerful add-in for WPS Office that integrates AI capabilities into your data analysis process. Follow these simple steps to get started with AI-driven data analytics using Excel Labs:

Step 1: Download and Install Excel Labs Add-In

Excel Labs

Step 2: Activate Excel Labs in WPS Office

Add add-ins WPS

Step 3: Generating AI-Driven Text

In any cell of your spreadsheet, enter the formula:


AI-Driven Text

Step 4: Fine-Tuning AI Text Generation (Optional)

You can use the extended formula:

=LABS.GENERATIVEAI("Text_Prompt", Temperature, Max_Tokens, Model)

Fine-Tuning AI Text Generation

Step 5: Analyze AI-Generated Text

By following these steps, you can effectively use Excel Labs to leverage the power of AI for data analytics in your WPS Office spreadsheets. Experiment with different prompts and fine-tuning options to get the most out of AI-driven text generation for your data analysis needs.

Part 3: The 5 Great AI Data Analysis

  1. WPS AI – Spreadsheet

WPS AI website

WPS AI is a powerful AI-driven spreadsheet tool that serves as an excellent alternative to MS Office. It offers a wide range of functions and features that enhance data analysis and processing. Here's an overview of WPS AI's key aspects:

  • Functions: WPS AI provides comprehensive spreadsheet functionalities, including data entry, formula calculations, and advanced statistical analysis.

  • Features: It incorporates AI technology to automate tasks like data cleaning, pattern recognition, and predictive modeling. It enhances accuracy and efficiency in data analysis.

  • Pros and Cons: WPS AI is free to use and compatible with all Microsoft file formats. However, some advanced AI features may require a subscription.

To download WPS AI:

Step 1: Visit the website https://www.wps.ai/

WPS AI website

Step 2: Log in to your WPS account and fill in the information

WPS AI waitlist

Step 3: Wait for the email from WPS

Step 4: Once your pass WPS review, you will receive an email

WPS AI email

Step 5: Click the download button in the email and start download

WPS AI download

Step 6 : Install and enjoy WPS AI

2 .  Tableau

Tableau website

Explore Tableau, a renowned data analysis tool with cutting-edge features. Discover how Tableau simplifies data visualization, interactive dashboards, and data exploration, making it a top choice for professionals in the field.

  • Functions and Features: With Tableau, users can easily connect to various data sources and generate dynamic charts, graphs, and maps. It supports drag-and-drop functionality, data blending, filtering, and advanced analytics.

  • Pros and Cons: Tableau offers a user-friendly interface, robust visualization capabilities, and compatibility with different data sources. However, pricing and learning curve for advanced features can be considerations.

3 .  Microsoft Power BI

Microsoft Power BI website

Uncover the capabilities of Microsoft Power BI, a comprehensive business intelligence tool. Learn how Power BI enables you to transform raw data into meaningful insights through interactive reports and visually appealing dashboards.

  • Functions and Features: Power BI offers functions for data modeling, preparation, and visualization. Users can create interactive reports, charts, and maps using an intuitive drag-and-drop interface. It also provides advanced analytics capabilities like predictive analytics and natural language querying.

  • Pros and Cons: Power BI integrates seamlessly with other Microsoft products, has a user-friendly interface, and offers strong data visualization capabilities. However, advanced features may have a learning curve, and its licensing and pricing structure can be complex.

4 .   IBM Watson Analytics

IBM Watson Analytics website

Discover the power of IBM Watson Analytics, an AI-powered platform that enables data discovery, predictive analytics, and data-driven decision-making. Find out how Watson Analytics can enhance your data analysis efforts.

  • Functions and Features: It offers data preparation, predictive modeling, and natural language querying. Users can create interactive dashboards, visualizations, and get automated insights.

  • Pros and Cons: IBM Watson Analytics excels in handling complex data, predictive capabilities, and natural language interface. It integrates with various data sources and supports collaboration. However, the learning curve may be steep, and customization options could be limited.

5 .  Google Cloud AutoML

Google Cloud AutoML website

Explore the capabilities of Google Cloud AutoML, an automated machine learning tool that empowers users to build custom AI models for data analysis. Discover its features and advantages for data scientists and analysts.

  • Functions and Features: It provides an intuitive interface and automates tasks like data preprocessing, model training, and deployment. It offers pre-built models for various tasks and allows users to create custom models with their own datasets.

  • Pros and Cons: Google Cloud AutoML is praised for its simplicity and seamless integration with other Google Cloud services. However, customization options may be limited compared to building models from scratch, and pricing can vary.



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Part 4:The Benefits of Using AI Tools for Data Analysis

Using AI tools for data analysis offers numerous benefits that enhance decision-making:

  1. Speed and Accuracy: AI tools process data quickly and with high precision, minimizing errors.

  2. Advanced Analytics: AI tools utilize sophisticated algorithms to uncover patterns and trends in complex data.

  3. Data Exploration and Visualization: AI tools provide intuitive interfaces and visualizations for easy data understanding.

  4. Predictive Analytics: AI tools can forecast future trends and outcomes based on historical data.

  5. Automation and Efficiency: AI tools automate repetitive tasks, saving time and improving productivity.

  6. Scalability and Adaptability: AI tools handle large and diverse datasets, adapting to changing business needs.

  7. Decision Support: AI tools offer insights and recommendations to aid decision-making.


Q1: How Does AI Data Analysis Differ from Traditional Data Analysis ?

AI data analysis differs from traditional data analysis in the following ways:

AI Data Analysis

Traditional Data Analysis

Relies on advanced algorithms

Manual processing

Fast processing and scalability

Slower processing, limited scalability

Automation of tasks (e.g., data cleaning, model building)

More manual effort required

Excels at pattern recognition

Relies on traditional statistical methods

Predictive capabilities for forecasting

Focuses on descriptive statistics

Adaptability and continuous learning

Limited adaptability

Handles large volumes of data

May struggle with large datasets

Q2: Can I use AI Data Analysis for free ?

Yes, there are free AI-powered data analysis tools available. We highlight WPS AI as a notable example of a free tool that offers robust data analysis capabilities.


In summary, this article explored the world of AI data analysis and introduced five amazing AI tools for data analysis. From WPS AI to Tableau, Microsoft Power BI, IBM Watson Analytics, and Google Cloud AutoML, each tool brings unique features and advantages to the table. Emphasizing the versatility and free availability of WPS AI, this guide provides valuable insights for data analysts seeking to harness the power of AI in their analytical endeavors. Upgrade your data analysis skills and unlock new possibilities with AI-powered tools today.

15 years of office industry experience, tech lover and copywriter. Follow me for product reviews, comparisons, and recommendations for new apps and software.