Good business decisions depend on actionable, objective insights. In fact, research by Gartner shows that organizations that build applications by leveraging a data analytics ecosystem will beat competitors.
To help you build a robust data ecosystem for analytics, we’ve created a short list of the best data analytics tools. But first, let’s look at some considerations you need to know to make a well-informed decision about what data analytics software is best for your business.
Table of contents:
As customer needs evolve, you should invest in data analytics solutions that help you find innovative ways to drive stronger, sustainable business performance. Here are some factors that can help you get a better ROI.
1. Focus on scalability
Your company and customers generate enormous volumes of data, which will only continue to grow with your success. That requires a scalable data analytics solution. Moreover, as your business grows, you need a single source of truth that helps your team gain a comprehensive view of your data. With a scalable data analytics tool, you can find insights from large datasets without losing time and performance. Look for a tool that has both technical scalability with data volumes and business scalability with business users.
2. Check data compatibility
According to research by Deloitte, nearly 60% of business leaders don’t believe they can even access or use their company’s data with their existing tools and resources. If your tool for data analysis is not capturing information from all sources, it creates data silos—reducing transparency and hampering decision-making. Having a data analytics tool that offers compatibility with multiple databases and sources helps your team create their own data pipelines and focus more on data-driven decisions.
3. Watch out for security features
Studies by McKinsey have shown that cybercrime costs will reach about $10.5 trillion in 2025—a 300% increase from 2015. This emphasizes the importance of security features in your modern data stack. Choosing a secure platform allows you to protect sensitive data and assets from authorized users and activate an incident response plan for threats and emergencies.
4. Ensure real-time dashboard and reporting
Interactive data visualizations are key for creating compelling data stories. A visualization platform allows business users to explore, understand, and communicate meaningful insights without seeking any help from IT. This drives more business value by enabling data teams to focus on high-impact projects. With an intuitive user interface, you can create dashboards and reports with elements such as drill-downs and filters to help you keep track of real-time KPIs, bringing insight to action at the point of decision-making.
5. Compatibility with AI-driven technologies
Moving beyond the hype, Generative AI is becoming a transformative tool for companies. Modern data analytics platforms harness the power of large language models (LLMs) for uncovering trends, giving relevant suggestions, and empowering every business user to supercharge their data story. By choosing a tool with AI-powered capabilities, you can ask complex business questions in natural language to search for content across your analytics catalog, create charts and visualizations, get AI-powered answers, build data models, and more.
6. Check user reviews
Before investing, it is critical to read user reviews from reputable sources such as Gartner Peer Insights and G2 to get up-to-date information about the platform’s capabilities, performance, and customer support. Users often share real-world scenarios in their reviews, demonstrating how the platform performs in practical situations. This can provide valuable insights into whether the platform aligns with your business needs.
Research by McKinsey shows that executives spend 40% of their time making decisions. By leveraging data analytics software, you can get the insights you need to make strategic decisions—saving time and money.
With a 4.6 rating on Gartner Peer Insights, ThoughtSpot’s analytics platform offers an intuitive search experience that makes data exploration and analysis accessible for everyone on the team—business users welcome. Powered by large language models like GPT and Google PaLM, the platform enables self-service analytics at an enterprise level. Additionally, you have granular control over data security with a centralized governance system that prevents unauthorized access and improves transparency. With just a few clicks, you can easily integrate ThoughtSpot into your existing data pipeline and generate real-time, interactive Liveboards.
Don’t just take our word for it—consider Wellthy. Before, the company’s customers used legacy business intelligence tools that required Python and SQL input. However, their already busy data team was overburdened with ad-hoc requests and was not able to implement larger data initiatives. Thanks to ThoughtSpot, Wellthy’s data felt liberated to ask questions and freely explore data. This helps the company save over $200k by increasing analyst efficiency and even empowering front-line business users to find their own insights.
Core features:
AI-powered, natural language search on your business data
Personalized, interactive Liveboard and reporting
Mobile app availability for insights on-the-go
Seamless integration with cloud data sources
Embedded analytics for product development
Data modeling and exploration
Security and governance controls
Try ThoughtSpot’s free trial to innovate rapidly with AI-powered analytics and generate and share insights across your team.
Mode’s Notebook interface and Visual Explorer allow you to connect to your database, run queries, and turn raw data into interactive visualizations for faster ad-hoc analysis. Mode has Notebooks for SQL, Python, and R, giving data teams the ability to work with data their way. Their visualization library offers advanced analytics capabilities to help business users explore data and get instant insights.
Here’s how Honeycomb increased its product stickiness with Mode:
The company faced issues analyzing large datasets as they had disjointed data sources and were manually querying product data with Metabase. To make better business decisions and keep up the pace, they switched to Mode.
Mode connected all of Honeycomb’s data sources in one place, allowing the team to ask questions and get answers about their product usage. They also leveraged Mode’s Notebook environment to slice data and build visualizations using Python. For Honeycomb’s team, querying and joining data in SQL and then exploring and visualizing in Python proved valuable in understanding customer behavior and crafting a better product strategy.
Core features:
Connectivity with multiple databases
Intuitive SQL editor to run and format multiple queries
Data view to understand query results
My work to search all your past queries
Visual explorer to help you build charts, graphs, and tables
AI-based assistance
Make smart, data-driven decisions about your product usage and understand your customer journey with Mode’s free trial.
Looker, Google’s tool for data analysis, can't keep up with Tableau’s viz or ThoughtSpot’s natural language queries and self-service analytics, but it does well as a semantic layer. Google has transitioned the product to Looker Modeler, which enables data teams to build common semantic models that provide a governed and trusted source of truth to leading analytics tools. ThoughtSpot is one of the first analytics to fully integrate with Looker Modeler.
Core features:
Data visualization
Embedded analytics
Integration with Google Workspace
Data modeling
Multiple database integration
Tableau is a visual data analytics platform known for its vast library of interactive dashboards. With its drag-and-drop interface, you can customize the look and feel of visualizations with formatting options that help you discover insights. Tableau users can also connect to multiple data sources, helping them perform statistical analyses and build predictive models. All-in-all, Tableau is known for helping skilled technical users, like analysts and developers, create pixel-perfect visualizations. However, for business users, the setup is practically impossible as they have to learn skills.
Core features:
Data visualization
Advanced data management (Security and scalability)
Embedded analytics
Data preparation and exploration
Native data connectors
Report sharing
Its user-centric approach is where Sisense focuses on new features for NLQ but sometimes falls short, relying more on traditional dashboard-based reporting. It also offers developer tools like SDKs and APIs, which can be integrated into a product UI. You can store data in its proprietary Elastiacube or connect data from a cloud warehouse to create a single source of truth. This helps users prepare, visualize, and explore data.
While Sisense has its strengths, it may not always match the innovative features and adaptability offered by other BI platforms in the category.
Core features:
Git integration
Low-code interface to create dashboards, widgets, and reports
AI-powered exploration paths and explanations
Integration with cloud data sources
Embedded analytics
APIs and SDKs
Knime is an open-source analytics platform that supports 300+ diverse data sources, tools, and types. It’s also known for its data science and machine learning use cases that help users analyze data and predict future business outcomes. The workflow controls, machine learning algorithms, and drag-and-drop visualizations enable users to streamline tasks and make data-driven decisions. With a growing community, users can learn and explore different use cases and functionalities.
Core features:
Access data from multiple sources
Data cleaning and processing
Data modeling
Build reusable workflows
Embedded analytics
Python functionality
Excel is Microsoft’s widely popular spreadsheet software that lets users do surface-level reporting and visualization. From pivot tables to formatting, users can leverage multiple functions and plug-ins to identify outliers, spot trends, and create charts. The easy-to-use interface and Microsoft’s Copilot (AI-assisted technology) help users find insights intuitively.
While this software is robust, it does come with certain limitations. It cannot handle large datasets and provides limited options for visualization and exploration. Additionally, real-time data monitoring is not available, so decision-making relies on outdated insights.
As a result, Excel remains the go-to tool for basic reporting and visualization tasks. However, if you want to create interactive charts and visualizations from your spreadsheet data, you can connect ThoughtSpot to Excel to uncover granular insights with just a couple of clicks.
Core features:
Data entry and formatting
Pivot table
What-if scenario
Collaboration and sharing
Mobile app for on-the-go reporting
Intuitive interface
Charts and tables
All the tools mentioned above bring unique capabilities to the table. But to create a truly compelling data story, you need an all-in-one business intelligence platform—one that empowers your data team to sync data from multiple sources and helps your business team confidently analyze that data with AI-powered, search-based analytics. That’s why organizations like Wealthy and Neobanck use data analytics platforms like ThoughtSpot to lead successful data-driven transformations and innovate at scale.
Ready to join the ranks of successful, data-driven businesses? Sign up for ThoughtSpot’s 14-day free trial and empower your team to leverage data as a competitive edge.
