A comprehensive review by the Pitch Avatar to help entrepreneurs, managers, marketers, and sales professionals choose the AI analytics tool best suited to their needs.
To say that AI-powered big data analytics tools have revolutionized the business world might be an overstatement. Analysts – whether in business, politics, or sports – have always strived to stay ahead of the curve, equipping themselves with the latest technologies. Since the 1930s, it has become increasingly clear that the world is growing more complex, processes are accelerating, and the volume of data is expanding so rapidly that human capabilities alone are no longer sufficient to handle data effectively.
Anyone who dares to forgo AI-driven analysis in today’s data-heavy landscape risks drowning in information overload, missing key insights, and falling behind with delayed conclusions and recommendations.
It’s no surprise, then, that over the past year and a half, a surge of AI analytics tools has emerged, specifically designed to manage vast datasets in the business sector. These tools help gather insights about market trends, competitors, sales, customer behavior, and website visitors. They streamline data collection, sorting, pattern recognition, and forecasting.
A brief list of the core functions and capabilities of AI-powered analytics tools:
- Data collection, processing, systematization, and visualization
- Process analysis, pattern and anomaly detection
- Forecasting and scenario modeling
- Solution suggestion, comparison, and evaluation
Before handing over big data analytics to AI software, it’s essential to identify which tool best fits your specific tasks and conditions. Our alphabetically organized review is designed to help you navigate the AI analytics landscape with ease.
Altair
Altair offers a suite of solutions, tools, and platforms for collecting, processing, managing, and analyzing data. The toolkit supports the entire analytics pipeline - from data discovery, cleansing, and organization to advanced machine learning model creation, report generation, and results visualization. While mastering the entire Altair ecosystem may take time, its capabilities are worth the investment.
Alteryx
This platform is primarily focused on automating data collection, processing, and analytics, with strong integration options. It emphasizes data analysis and report creation, featuring a wide range of tools, functions, and system connectivity options.
Amazon QuickSight
Amazon QuickSight delivers analytics on-demand through natural language queries -- eliminating the need for complex setup or specialist training. It enables business analysts to create serverless dashboards and allows developers to build applications using its capabilities. It also supports collaborative work, seamless integration, and promises consistent performance regardless of usage volume.
Domo
A cloud-based platform centered on two key principles: 1) making business analytics accessible to users without technical expertise, and 2) providing real-time data to support agile strategy development. Domo also enables quick development of custom applications in addition to offering ready-made solutions.
SAP BusinessObjects Business Intelligence
A comprehensive BI suite for internal data collection, sharing, reporting, and visualization. Highly customizable and tailored for business use from the ground up, SAP BI is ideal for organizations seeking enterprise-grade analytics tools.
IBM Cognos Analytics
Packed with features, configurations, and integration capabilities, IBM Cognos is one of the most robust tools on the market. Notably, it allows users to pose analytical questions in natural language, increasing accessibility and user-friendliness.
IBM Watson Studio
An integrated hybrid environment for building and deploying AI models for data collection and analysis. It combines open-source tools like PyTorch, TensorFlow, and scikit-learn with IBM’s ecosystem. Best suited for data science professionals who know exactly what they want from AI analytics.
KNIME
A comprehensive data analytics platform offering model building, results visualization, 300+ connectors for data integration from diverse sources, and more. KNIME stands out for its ease of use, configuration, and deployment.
Looker
An interactive business analytics platform from Google Cloud, offering both ready-made solutions and custom app development that integrates into existing ecosystems. Looker focuses on data visualization and performance monitoring with flexible configuration for personalized user experiences and support for hundreds of data sources.
Microsoft Power BI
A business analytics and data visualization platform with a vast range of integrations, tools, and connectors. Includes an AI assistant capable of understanding natural language queries, simplifying data interaction.
MicroStrategy
A unified platform offering a suite of AI tools designed to accelerate all business processes involving data analytics and insights application. Features include an intuitive chatbot named Auto that processes natural language queries for streamlined operations.
Oracle Analytics
A full-cycle analytics service offering tools for data discovery, import, processing, modeling, reporting, and visualization. Deployable in cloud, on-premises, or hybrid environments, Oracle Analytics emphasizes security and collaborative capabilities.
Qlik Sense
Qlik Sense offers multiple formats for delivering analytics—from dashboards to natural language interfaces. Noteworthy features include data source synchronization and associative search capabilities. It promises high-speed insights for flexible, responsive business strategies.
Salesforce Einstein
A multifunctional AI tool built into the popular CRM platform. It uses machine learning and natural language processing for predictive analytics, focusing on customer behavior forecasting - e.g., identifying potential clients and their likelihood of converting. Other features include task automation and personalized customer interactions.
Sisense Fusion
A cloud-based analytics platform offering embedded tools and user-friendly visualizations. It covers the full analytics cycle - from multi-source data collection and sorting to decision implementation. With 30+ native connectors and unlimited scalability, Sisense Fusion claims seamless integration into any number of client products.
Tableau
A powerful analytics platform designed for comprehensive data processing and advanced insights. Offers deep integration into enterprise systems for accurate, holistic business intelligence. Supports a wide range of databases and includes Salesforce Einstein. Ideal for medium to large organizations with complex analytics needs.
ThoughtSpot
An easy-to-use analytics tool with intuitive setup and management, requiring no technical staff for deployment. One of its key features is the real-time visualization of insights on interactive dashboards.
SAS Visual Statistics
A cloud-based platform with open-source support, offering customizable descriptive and predictive models, including decision trees. True to its name, it presents statistics and analytics in a clear, visual format.
While the AI analytics tools covered in this guide – and those not mentioned – are highly advanced, none of them are crystal balls that will reveal a flawless, winning business strategy. They can uncover behavioral patterns of customers, competitors, and employees – but they can’t read minds.
No matter how thoroughly these systems analyze data, creative business ideas and groundbreaking strategies still come from people. Relying solely on AI analytics helps optimize existing solutions. But true innovation – breakthroughs, original ideas, and bold decisions – still belong to human insight. So, don’t worry – human business analysts aren’t going anywhere just yet.
Wishing you all the best and much success!
