Top 9 Augmented Analytics Tools for 2025

As artificial intelligence (AI) continues to speed up business operations, augmented analytics is the next wave of revolution. One major area where AI is making a difference is by augmenting business intelligence (BI). 

The result? Analytical tools that are augmented with AI are more powerful than previous generations of BI—and it’s shifting how companies interpret information. Here’s what you need to know about augmented analytics and augmented analytics tools. In this article, we’ll also explore the top 9 augmented analytics platforms of 2025. 

What is augmented analytics?

 Augmented analytics is a type of data analytics that uses AI, machine learning (ML), and natural language processing (NPL) to help understand data and make better business decisions. These types of AI augment data analytics; hence, the term augmented analytics. 

Like many other kinds of automated work, augmented analytics is useful for sorting through massive amounts of information in a much shorter time than it would take a person to do it. People can use augmented analytics to expand the extent of the data they work with. Augmented analytics can help with data collection, organization, and preparation, as well as modeling, insight generation, and insight explanation. The main goal is to understand data better in order to make better business decisions, save money, and help people focus on tasks that drive the organization toward its goals faster. 

However, unlike human data analysts, augmented analytics doesn’t have bad days or personal biases. It makes decisions solely based on data, making connections and noticing patterns that the human eye might overlook.

What are augmented analytics tools?

Augmented analytics tools are software that use augmented analytics to find patterns and make predictions, helping people make more informed business decisions and accurate predictions. 

Rather than having humans digging through massive amounts of data and downloading hundreds of spreadsheets, augmented analytics helps companies organize data, visualize information, and notice trends. For example, companies can use augmented analytics to understand why some store locations are more profitable than others, predict which products will sell the most, find underlying reasons why a competitor may be outpacing your company, and gain many other insights. Augmented analytics tools are built to synthesize, compile, clean, organize, visualize, and understand data in faster, more efficient ways than were possible before. 

While augmented analytics are transforming how companies collect and visualize data, the tools are also changing how people work with data. You no longer have to work in IT or have the job title of data analyst to work with these charts and graphs; augmented analytics synthesizes and summarizes data in ways that are simple enough for anyone to understand, even without a coding background. This trend is making data accessible to parts of organizations that previously didn’t collect or use data very often. 

Most augmented analytics tools are entirely self-serve, meaning that people can create models, export reports, and slice and dice numbers whenever they need to. The freedom to access and work with data anytime means that anyone in the organization can make decisions based on the most up-to-date, real-time information and get the most accurate predictions. As employees increase their data literacy, companies start making smarter business decisions across the entire organization. 

When organizations invest in augmented analytics tools, here are some of the benefits they gain:

• Automated workflows
• Increased data democratization and data literacy 
• More objective and unbiased insights from data
• Cleaner data
• More accurate predictions
• Increased savings from fewer data analyst positions and more automated tasks 
• Freer IT teams who don’t have to create and distribute reports

Top 9 augmented analytics tools for 2025

To get the most out of your data, you’ll need the best augmented analytics tool for your company. Many companies have started offering tools infused with AI and ML, but some are better than others. The best tool for you may depend on the amount and type of data you’re dealing with, how collaborative your teams are, and what kinds of other platforms you want to integrate the tool with. Here are the top augmented analytics tools for 2025. 

1. Domo

Domo’s cloud-based platform is among the best augmented analytics tools due to its ability to create data-based apps that facilitate various business activities directly at the point of execution. The AI augmentation helps Domo’s solutions extract data insights in real time by cleaning up data sets, finding actionable insights, and identifying trends. Without any prior coding experience, users can build out dashboards and easily share them with team members. Domo is also great for automating workflows and implementing ModelOps. 

Pros:

• High-performing data aggregation
• A pay-for-what-you-use system and a credit system to make the product affordable and shareable
• Integrates well to combine data from many different sources

Cons: 

• Rigid data structures; it’s difficult to change the off-the-shelf charts 
• Setting up back-end integrations takes a while

2. ThoughtSpot

ThoughtSpot’s augmented analytics tools were made to replace clunky old BI tools with something more modern and streamlined. ThoughtSpot’s main augmented analytics tool, SpotIQ, uses a parallel in-memory calculation engine to analyze billions of rows of data and execute dozens of insight-detection algorithms in seconds. ThoughtSpot Sage is another augmented tool that uses ChatGPT’s natural language processing and generative AI capabilities to enhance its self-serve analytics platform. 

Pros: 

• An intuitive interface and nice aesthetics make it easy to use for non-technical people in your organization
• The integration with ChatGPT is a major plus
• Users can make visualization boards and share data with teammates quickly 
• Fast setup and quickly loading dashboards
• Excellent for small- and medium-sized businesses

Cons: 

• On the simple side. Larger organizations may need more customization, technical capabilities, and data details than ThoughtSpot provides 
• The scalability of the product isn’t powerful enough for major companies 

3. Alteryx

The whole mission of Alteryx is to make data more digestible. In 2022, the company doubled down on that promise by adding augmented analytics to its tools. Fast forward to today, and Alteryx now offers augmented analytics with many of its products, including Designer Desktop, Designer Server, Designer Cloud, Connect, and a variety of other spatial analytics tools. The no-code, drag-and-drop functionality makes Alteryx a great choice for data visualization and data automation. 

Pros: 

• Great integration. The augmented analytics tools help automate analytic processes to output to 70-plus tools, including SQL, Excel, and Azure 
• Drag-and-drop analytics for Snowflake, Excel, databases, and more
• Low-code/no-code data science

Cons: 

• Steep learning curve 
• Limitations and performance challenges on large data sets and highly customized models

4. AnswerRocket

AnswerRocket knows that traditional analytics aren’t enough for its search-powered data analytics. Augmented analytics help AnswerRocket offer deeper, faster insights to help you make business decisions faster. The platform integrates natural language processing, machine learning, and graphical processing units to analyze data sets, visualize data quickly, and understand the intent behind a user’s question.   

Pros:

• The data analysis of AnswerRocket is one of the best on the market
• Easy automation for real-time insights
• Connects well with lots of platforms, including Amazon Redshift, SQL databases, Google Drive and Google Analytics, Oracle, SAP, Salesforce, Snowflake and more

Cons: 

• Limited to no customer support or community
• Natural language processing is helpful but still has some issues 

5. Microsoft Power BI

One of the big advantages of using Microsoft Power BI is its familiar feel; it uses the same features and formatting as Microsoft’s other tools like Excel, PowerPoint, and Office 365. This makes it easy to import, model, visualize, and share data to uncover insights — all within the same tool. The augmented analytics features help clean data, find trends, and suggest business decisions. Both cloud-based and on-prem capabilities are available. 

Pros:

• Active support community and support
• Solid security features
• Flexible and customizable modeling and reporting options
• Easy creation of visuals
• Highly collaborative 
• Uses Excel for reporting, which integrates perfectly because it’s all from Microsoft 

Cons: 

• Can be slow, especially with large data sets
• Not a great user interface. Has a lot of options, but the menus are crowded and cluttered

6. Pyramid Analytics

Pyramid Analytics’s augmented analytics turn augmented AI into augmented BI with automated trend analyses. Although it’s great for data, the focus is just as much on governance and self-service capabilities. The AI “explain” feature helps explain the reasons for underlying differences between any two data points, which helps the platform deliver holistic insights, understand anomalies, provide descriptive and diagnostic analysis, and display data drivers.

Pros: 

• Has more than 200 connectors to integrate with your existing platforms
• Easy modeling and fast visualizations
• Flexible and granular data accessibility
• Helpful reporting with features like AI-augmented tabular SQL development and one-click regression lines

Cons:

• Difficult to navigate and has a rough UI
• Still has bugs regularly after updates 

7. Qlik

Harness the full potential of your data with Qlik’s automated insight generation, natural language interaction, predictive analytics, and generative AI. Qlik has several augmented analytics tools, including Qlik Cloud Analytics, Qlik Sense, Qlik Insight Advisor, and Qlik Data Catalyst. Overall, the platform offers a variety of BI tools with embedded functionality.  

Pros:

• Scalable and fast
• Great at extending and embedding visual analytics in existing applications and portals
• Ability to mix heterogeneous datasets easily

Cons:

• Does not export to Excel
• Integration limitations. Lack of python scripting integrations and limited integration with Cloudera Data Science Workbench (CDSW)

8. SAP Analytics Cloud

Historically, SAP has been a leader in enterprise resource planning (ERP), so it makes sense that SAP’s augmented analytics tools are focused on de-risking business projects, accelerating business outcomes, and implementing AI-supported best practices. SAP Analytics Cloud uses generative AI to automate reporting, discover hidden insights, and create and develop business plans as well as unite data reporting and planning across multiple functions of the organization. 

Pros:

• Variety of built-in modeling tools to inform business decisions
• High processing speed
• High-quality natural language querying

Cons: 

• No mobile app
• Poor sorting and filtering capabilities

9. Sisense

Sisense believes that data and insights should be available to everyone, regardless of technical ability. Sisense’s no-code/low-code platform uses augmented analytics to make BI more accessible. The Sisense Fusion and Sisense Pulse tools use AI to seamlessly blend into workflows, help visualize data, and polish insights for business decisions. The augmented analytics add-ons include data preparation through ElastiCube and augmented text deduplication.

Pros:

• UI for users is intuitive and simple 
• Easy integration 
• Customization and drag-and-drop features make modeling fast and easy

Cons:

• Pulling reports is difficult
• The admin side is complicated 

Augmented analytics tools represent a significant leap forward in how organizations harness data to drive decision-making. By integrating AI and machine learning, these tools empower users across all levels of an organization—regardless of technical expertise—to glean insights from vast data sets quickly and efficiently. Choosing the right tool for your specific needs will not only streamline your analytics processes but also position your business to thrive in an increasingly data-centric landscape. Embrace augmented analytics and unlock the full potential of your data for smarter, more informed business decisions with Domo.