10 AI Data Analytics Tools Transforming the Industry in 2024

Today, data is growing exponentially every second. This data, if analyzed effectively, can unlock a wealth of insights. But the sheer volume makes it a daunting task. That’s why we need AI data analytics tools to deal with such massive data.

But what exactly are these tools, anyway? You’ll find the detailed answer in our article. 

In this article, we’ll start with the definition and benefits of AI data analytics. We’ll then delve into the latest trends in AI data analytics and what the future holds. And, of course, this article also introduces you to the top 10 AI data analytics tools in 2024.

So, if you’re intrigued by the power of AI in data analytics and want to know about the tools that are making a difference, stay tuned!

Understanding AI Data Analytics

In the first section, we’ll discover the fundamentals behind AI data analytics. 

What are AI & Data Analytics?

Data Analytics is the process of methodically using logical and statistical techniques to describe, depict, and assess data. 

It involves the collection, cleaning, and analysis of data to extract valuable insights that would otherwise be lost in the mass of information. These insights, accordingly, enable your business to make more informed decisions.

Meanwhile, Artificial Intelligence (AI) represents the emulation of human cognitive functions by machines, predominantly computer systems. 

These functions encompass learning (which gathers data and the guidelines for its application), reasoning (which employs these guidelines to draw informed conclusions), and self-correction. Accordingly, AI can learn and adapt from data, which sets it apart from traditional computational systems.

How Can AI & Data Analytics Work Together?

AI and data analytics can work together to create powerful synergies. AI, with its ability to learn from data, can automate and optimize the process of data analytics. 

Navigating through large amounts of data, this advanced tech discovers patterns or trends and then delivers insightful conclusions quickly and accurately. This capability far exceeds what humans can do, thereby promoting the widespread adoption of AI in data analytics.

This led to the launch of AI data analytics tools. In today’s data-driven world, the need for these tools is more important than ever before. 

They can handle large volumes of data, uncover hidden patterns, and provide valuable insights, all while reducing the time and resources required for traditional data analysis. This makes them indispensable for any organization looking to leverage their data effectively.

FURTHER READING:

1. Data Science vs Data Analytics: A Detailed Comparison

2. What is Healthcare Data Analytics? A Detailed Guide

3. 10 Best Master’s in Data Analytics to Advance Your Career

The Role and Benefits of AI in Data Analytics

To better understand why data analytics tools are increasingly integrated with AI capabilities, let’s delve into the immense benefits of AI in these tools:

Automating Mundane Tasks

AI has permeated the business sector, with 51% of companies employing it for business process automation. Especially in the realm of data analytics, AI is instrumental in automating tasks that are often mundane and repetitive.

One of the key areas where AI proves its worth is in the automation of data cleaning and preparation. These processes, when performed manually, are not only time-consuming but also susceptible to errors. By automating these tasks, AI significantly enhances the accuracy and efficiency of data processing. Also, it can free up time for data analysts to focus on more complex tasks. 

Advancing Pattern Recognition

AI algorithms help your business identify hidden patterns, trends, and anomalies in data that might be missed by humans. This advanced pattern recognition capability can lead to new insights and discoveries, enabling your business to make more informed decisions.

Fostering Predictive Analytics

Predictive analytics is a field that detects future outcomes by using data, statistical algorithms, and AI/ML techniques. 

By analyzing historical data, AI can predict future trends and behaviors, helping businesses to make proactive, data-driven decisions. This predictive capability can be particularly useful in sales forecasting, risk management, and operational efficiency.

Improving Accuracy and Efficiency

AI can significantly enhance the accuracy and efficiency of data analysis processes. By automating data cleaning and analysis tasks, AI reduces the risk of human error, leading to more accurate results. 

Moreover, AI can process and analyze data much faster than humans, leading to increased efficiency. This improved accuracy and efficiency can result in better decision-making and increased business performance.

Democratizing Data Analysis

AI is democratizing data analysis by making it accessible to non-technical users. With AI data analytics tools, users without a background in data science can extract valuable insights from data. These tools often come with intuitive interfaces and automated features, enabling users to analyze data and generate reports with ease. 

This democratization of data analysis is empowering more people to make data-driven decisions and is fostering a culture of data literacy across organizations.

Latest Trends and Future in AI Data Analytics

The advantages of using AI in data analysis are undeniable. This encourages more software providers to add AI features to their data analysis tools to enhance their clients’ work. 

Today, nearly half of the companies surveyed by ThoughtWorks define a data product as something that includes data analytics and AI, rather than merely considering AI as an add-on. This shift in perspective shows that many data analysis firms now see AI as a crucial component of their services. 

As this trend continues, we can see current developments in AI data analytics tools that will influence their future direction.

The Rise of Generative AI

Since its introduction in November 2022, no one might think ChatGPT can become the fastest-growing tech in the history of web apps. This has led to the later development of Generative AI, or GenAI. This AI model helps detect patterns in existing data and generate new content based on given prompts. 

Precedence Research reports that the global market GenAI in analytics was valued at USD 724.5 million in 2022 and is expected to grow with a CAGR of 28.51% from 2023 to 2032. 

The main driver behind this growth is its standout features (e.g., data accessibility). In the recent AWS survey, 80% of the companies also said that GenAI will revolutionize their organizations. So in the future, this demand for GenAI in data analytics will increase to ensure fast, accurate decision-making.

Despite the high level of enthusiasm for GenAI, it has yet to deliver significant value. Of course, the production deployment of GenAI will require more than just experiments; it’ll require additional investment and organizational change. Also in the AWS survey, 93% of the companies agreed that a data strategy is critical to deriving value from GenAI. Therefore, companies still have a long way to harness the full power of this tech for data analytics.

Focus on Data Security & Accuracy

McKinsey’s survey revealed that businesses identify inaccuracy and cybersecurity as the two most significant risks associated with AI. Indeed, AI solutions that generate data or output often lack thorough examination and validation. This oversight frequently results in subpar outcomes, including erroneous, inapplicable, and questionable results. Besides, if the training data is biased, AI models may deliver inaccurate outputs.

Many companies are realizing these problems and attempting to mitigate them. The proof is half of the companies today are reducing the risks of inaccuracy and cybersecurity arising from AI during data analytics. Looking ahead, this will remain a significant concern, and businesses will implement more measures to ensure the accuracy and security of AI data analytics tools.

Top 10 Leading AI Data Analytics Tools in 2024

As we navigate through the era of digital transformation, AI data analytics tools stand at the forefront, revolutionizing the way businesses operate. 

So what tools are worth your investment? This list will provide you with an in-depth look at the best ones in 2024.

Microsoft Power BI

Microsoft Power BI is a software suite that has business intelligence capabilities to turn your unrelated sources of data into consistent and interactive insights. It provides a consolidated view of essential business data, connects to numerous data sources, simplifies data preparation, and facilitates ad hoc analysis. Power BI generates attractive reports and publishes them for your organization to access on the web and mobile devices.

Key Features

• Copilot: Swiftly generate comprehensive reports based on your prompts. Visually present data summaries, create DAX (Data Analysis Expressions) experiences, and provide straightforward answers.
• Microsoft 365 Integration: Allow your organization to share insights across Office 365 or Microsoft Teams, enabling everyone to make data-driven decisions.
• Microsoft Fabric Integration: Revolutionize your organization’s data management with Microsoft Fabric. Allow Power BI users to integrate their workflows with version control systems like Git, fostering efficient team collaboration.

Pricing Plans

• Free Account: Allow free signup and offer the power of interactive, visually rich reports at no cost.
• Power BI Pro: For just USD 10.00 per user/month, access shared Power BI reports and publish your own for a broader impact.
• Power BI Premium Per User: Starting at USD 20.00 per user/month, license specific users with features designed for enterprise-scale needs.
• Power BI in Microsoft Fabric: Allow report sharing with those having no Pro License through Power BI Premium Capacity or access to Microsoft Fabric workloads. Pricing details vary.

Tableau

Tableau is a robust data visualization tool utilized in the Business Intelligence industry. It helps convert raw data into a format that’s easy to understand without any technical skills or coding knowledge.

Key Features

• Einstein Copilot: Democratize data analytics across your organization and make insights more comprehensible at every level. Enable admins to confidently leverage AI-powered experiences, all while maintaining stringent data security.
• Tableau Pulse: Equip every employee with intelligent, personalized, and contextual insights delivered in their workflow.
• Tableau Mobile: Enable you to monitor your metrics on the go and explore personalized data insights.
• Dynamic Axis Ranges: Allow axis ranges of your charts to change dynamically based on the values in your workbook. This then enables more dynamic visualizations when your data often changes.
• Multi-row Calculations in Tableau Prep: Carry out table computations during your data preparation phase. 

Pricing Plans

• Tableau Creator: This plan offers such products as Tableau Desktop, Tableau Pulse, Tableau Prep Builder, and Tableau Cloud (with one Creator license). Start with USD 75 per user/month if you’re billed annually.
• Tableau Explorer: This plan offers such products as Tableau Pulse and Tableau Cloud (with one Creator license). Start with USD 42 per user/month if you’re billed annually.
• Tableau Viewer: This plan allows you to access visualizations in a safe platform. Start with USD 15 per user/month if you’re billed annually.

IBM Watson Studio

As one of the best AI data analytics tools, IBM Watson Studio empowers you to build, execute, and administer AI models to deliver insightful decisions anywhere on IBM Cloud Pak for Data. It integrates open-source frameworks (e.g., TensorFlow or PyTorch) with IBM and its ecosystem tools to implement data analytics. 

Key Features

• Streamlined Experimentation with AutoAI: Experience the power of automated model pipeline construction. From data preparation to model type selection, and from generation to ranking of model pipelines, AutoAI accelerates your experimentation process.
• Advanced Data Refinery: Use an intuitive graphical flow editor to clean your data. Leverage interactive templates to code operations, functions, and logical operators seamlessly.
• Visual Tooling Integration: With IBM SPSS Modeler in Watson Studio, prepare your data swiftly and develop models visually.
• Decision Optimization Embedded: Merge predictive and prescriptive models to optimize decisions using predictions. Create and modify models in Python, OPL, or even with natural language.

Pricing Plans

IBM offers two Watson Studio versions, including:

• IBM Watson Studio on IBM Cloud Pak for Data: This version allows for various licensing options and platform deployment on private or public cloud. Its price isn’t public, so you need to contact IBM for further information.
• IBM Watson Studio on IBM Cloud Pak for Data: This one offers a set of fully managed services you may access on the IBM public cloud. It has two pricing plans: Lite – a free one for only one user & Premium – a paid one for unlimited users at USD 1.02 USD per CUH (Capacity Unit Hour).

MonkeyLearn

MonkeyLearn is a cloud-based text analytics tool that extracts valuable data from various text sources (e.g., emails or surveys) and transforms it into personalized visualizations. The platform provides insights and workflow automation for support, product, customer experience (CX), and development teams, and can be integrated into in-house applications. 

Key Features

• Pre-Built & Custom Machine Learning Models: Opt for pre-configured models or tailor your own for your needs. 
• Fast Data Visualizations & In-depth Insights: Uncover immediate insights as you analyze your data and customize visualizations based on your preferences.
• Text Analytics with Available Business Templates: Explore a wide range of templates, each designed for unique business contexts and equipped with ready-to-use text analysis models and dashboards. Simply integrate with your apps and BI tools using our native integrations, SQL connection, or API.
• Integration With External Sources: Seamlessly connect with multiple apps like Zendesk, Medallia, and Google Sheets to conduct data analytics and automate business workflows.

Pricing Plans

• Team: Start with USD 299 per month for 10K queries.
• Business: The price depends on your business needs. So, contact MonkeyLearn for further information.

Akkio

Akkio is a Generative Business Intelligence (BI) tool revolutionizing how we work with data. Now anyone can harness the power of AI and machine learning to chat with live data, automatically generate charts and dashboards, and precisely forecast key business outcomes with next-generation speed and accuracy.

Key Features

• AI Capabilities: Incorporate all data sources (e.g., MongoDB, Amazon Redshift, or PostgreSQL) and automatically update data. Provide predictive models to build instantly strategic, actionable insights from your data and deliver auto-updated reports to clients.
• Chat Explore: Generate insightful answers from the dataset in real-time with the support of the built-in GPT-4 chat.
• Generative Reports: Automatically build instant reports right after you connect your data with Akkio and describe the issue or app you’re working on. These reports offer solutions for marketing spend optimization, sales forecasting, and more. 
• Chat Data Prep: Use prompts to clean data, reformat dates, combine columns, and more without the need for coding.

Pricing Plans

Akkio’s pricing packages are designed for three different user groups:

• Users: This plan provides team members with two options: Basic at USD 49 per user/month & Professional at USD 99 per user/month. 
• Organization Add-Ons: This plan offers custom add-ons to advance your company’s capabilities through two options. They include Build-On Package at USD 999 per business/month & Dedicated Server at USD 1,999 per business/month.
• Data Package Add-Ons: This plan allows all businesses to access 1M rows of connected data & 100K predictions for free per month. The more rows and predictions your business requires, the more you pay. 

Altair RapidMiner

Altair RapidMiner is one of the leading AI data analytics tools in 2024. It provides a pathway to modernization for established data analytics teams and a pathway to automation for teams that are just beginning their data journey. 

Key Features

• Automated Data Mining & Conversion: Automate the process of extracting and transforming your data into more accurate datasets within seconds. Remove error-prone, repetitive tasks and enhance tasks that add more value to your business.
• Data & Machine Learning Workflows: Swiftly create, train, evaluate, and deploy predictive & prescriptive models for your business data.
• Real-time Data Processing & Visualization: Instantly detect abnormal signals, trends, and outliers. Then use powerful, visual dashboards to present insights to all stakeholders across your business. This feature, accordingly, allows for quick, fully informed decisions based on vast amounts of rapidly changing inputs.

Pricing Plans

• Professional: Start at USD 7,500 per user/month on the cloud.
• Enterprise: Start at USD 15,000 per user/month on the cloud.
• AI Hub: Start at USD 54,000 per user/month on the cloud.

Dataiku

Dataiku is a comprehensive platform designed to facilitate the development, deployment, and management of data and AI projects across an organization. It serves as a collaborative workspace that brings together both technical and non-technical team members, enabling them to work together effectively on data projects.

Key Features

• Data Prep: Provide a wide set of data transformation, AI-based data prep, and other functions to connect, prepare, and clean data for analytics at any scale.
• Visualization & Analytics Apps: Offer self-service analytics that involves no-code apps, central workspaces, and dashboards. These services enable your analytics teams to share insights & data outputs with ease.
• Visual AutoML: Support your teams to build co-code ML models and explain model behavior through built-in explainability functions.
• GenAI Capability: Empower you to create enterprise-level, secure GenAI apps for your data projects.
• Extensibility: Enhance the platform’s native capabilities with plugins and custom applications. This then allows you to tailor Dataiku to your specific requirements.

Pricing Plans

Dataiku offers a free plan and three paid ones. But the company doesn’t specify the prices. These plans include:

• Free Edition: This plan is free forever and is suitable for up to 3 users. It allows you to install the platform on your infrastructure and access files or open-source databases.
• Discover Plan: This plan is designed for small teams of up to 5 users. It includes 20+ database connectors plus limited automation.
• Business Plan: This plan is intended for mid-sized teams of up to 20 users. It offers unlimited computations with Kubernetes, full automation, and advanced security.
• Enterprise Plan: This plan offers scalable automation and governance. It includes all database connectors, full deployment capabilities, an isolation framework, and unlimited resource governance.

Sisense

Sisense is one of the best AI data analytics tools in the world. It provides a unique business intelligence and analytics platform that helps users connect different data sources and perform complex queries in seconds. 

Key Features

• GenAI Chatbot: Suggest where to begin your data exploration, enhance analytics, request data, and receive answers in a natural language. Build your custom, LLM-powered Chatbot by using React Components & APIs to mix and match built-in GenAI building blocks.
• Actionable Intelligence: Integrate intelligence into your business’s workflows. Its goal is to facilitate data-driven decision-making by enabling all users to manage, visualize, and interpret their data within a single platform.
• Scalability: Allow the scaling of analytics across the organization with easy sharing of insights through dashboards.
• Sisense Quest: Enable you to implement sophisticated analytic models and then incorporate actions that can be executed by viewers directly from the dashboard. 

Pricing Plans

Sisense offers a flexible pricing plan based on your business’s requirements. So, you need to contact the company for further information. 

Polymer

Polymer is among the best AI data analytics tools known for its simplicity and user-friendliness. As a Business Intelligence (BI) platform, it eliminates the need for complex configurations and extensive learning periods. With Polymer, users can effortlessly create visual representations, construct dashboards, and professionally present their data.

Key Features

• Dashboard Creator: Empower you to craft personalized dashboards swiftly without coding or design expertise. Also, this feature provides a user-friendly drag-and-drop dashboard builder with a variety of chart types and flexible filter options.
• Polymer AI: Automate the process of data analysis and presentation of relevant insights. 
• Embedded Analytics: Allow the integration of data analysis directly into your business apps and software, making analytics and reporting an integral part of the user experience. With Polymer’s Embedded Analytics, you can create visually appealing charts and graphs that integrate seamlessly into your own apps and services.

Pricing Plans

• Starter: Starting with USD 25/month (billed annually), this plan is for 1 editor and 1 account per data connector.
• Pro: Starting with USD 50/month (billed annually), this plan is for 1 editor and 5 accounts per data connector.
• Teams: Starting with USD 125/month (billed annually), this plan is for 3 editors and 15 accounts per data connector.
• Enterprise: This plan is for a custom number of editors and unlimited accounts per data connector. So you need to contact the company for further information.

KNIME

KNIME is a complete platform for data analytics and science. This tool bridges the gap between dashboards and advanced analytics through an intuitive interface that is suitable for anyone working with data. It empowers more business experts to be self-sufficient and more data experts to push the business to the forefront of modern data science, integrating the latest AI and Machine Learning techniques.

Key Features

• KNIME AI Assistant (K-AI): Autonomously generate analytics workflows based on your instructions. 
• LLM Customization: Allow you to integrate and customize LLMs using your own data. This enables you to build AI-powered apps tailored to your specific use cases.
• AI Coding Assistant: This feature automatically generates Python scripts and visualizations, simplifying the handling of complex tasks.
• User-Friendly Interface: Its interface is designed to be easy to use, requiring little to no coding. This makes it suitable for users with different levels of programming skills.

Pricing Plans

KNIME offers two options based on your place of data management and deployment.

• KNIME Community Hub: This plan is for those managing data on KNIME. It offers two pricing plans, including a free one for individuals and a paid one for teams at USD 99 per month.
• KNIME Business Hub: This plan is for those installing the platform on their business infrastructure. It offers three pricing plans, including Basic for small teams with business needs at USD 39,900 per year, Standard for teams with many solutions at USD 71,250 per year, and Enterprise for enterprise-wide deployment.

Conclusion

This article unpacked the world of AI data analytics, explored exciting future trends, and introduced you to the top 10 tools that are changing the game in 2024. Now it’s your turn to set sail on your data adventure!  With the right AI data analytics tools at your side, you can unearth hidden insights and make discoveries that propel your business forward. So, dive in and start exploring these amazing tools today!