/ 12 Data Analytics Tools to Use in 2025

12 Data Analytics Tools to Use in 2025

Data analytics software example with several screenshots

With technology advances and increasing connectivity, data generation continues to rise. An estimated 97 zettabytes (ZB) of data were created globally in 2022, and that number is projected to rise to 181 ZB by 2025. Data empowers small businesses and multinational corporations alike but requires the right tools to make business decisions that drive growth and profitability. Processing, cleaning, analyzing, and visualizing large data volumes is challenging—but a data analytics platform, one that fits your requirements, can make it easier. 

What are data analytics tools?

Data analytics tools are software or applications that collect, process, and analyze data for a business, including data on its customers or clients and its competition. Analytics tools offer dashboards and visualizations to understand and explain data in actionable reports. 

Any data analysis program aims to discover insights, improve company processes or performance, and help leaders make better data-driven decisions to decrease costs and increase sales and profits. Businesses harness data analytics to understand their customers better, determine their pricing, know where to allocate resources, and more.

While many data analytics platforms have similar features and functionalities, analysts must know what type of data analysis they want to perform to find the best tool for their needs. There are five main types of data analytics:

  • Descriptive analytics: This type summarizes large, complex data sets into understandable patterns, trends, or distributions. It offers a historical view of the data and can spot anomalies and unusual patterns.
  • Predictive analytics: This type uses machine learning, predictive modeling, and statistical algorithms to forecast future outcomes. It can identify patterns or trends, help leaders make proactive business decisions, and help make risk assessments or predict opportunities.
  • Diagnostic analytics: Analysts use this type to find the root cause of a problem, trend, or past event. It also helps with fraud detection, troubleshooting, or optimization.
  • Cognitive analytics: This more advanced type of analytics uses machine learning and artificial intelligence to process and analyze large amounts of unstructured data sets, which other analytics tools may have trouble processing. This method can create predictions and develop insights for your organization. 
  • Prescriptive analytics: This method develops a course of action for your business based on the outcomes of predictive analytics. It supports decision-making through predictive modeling, real-time data analysis, and optimization. 

Once you know the type of analysis you want to perform, you also need to consider the volume and complexity of your data and your team’s expertise. Some tools only work well with smaller data sets and can’t scale as your business grows, while others offer more flexibility in services and scale. 

If non-technical professionals are utilizing data analytics tools, you’ll want to find an easy-to-use dashboard and visualization features that do not require coding or advanced skills to operate. Customization and easy integration with existing systems and third-party data sources are additional features to consider when selecting a data analytics tool.

Top 12 data analytics platforms 

Choosing the right data analytics solution can be a difficult task, requiring in-depth research into technical capabilities and features. To simplify this process, we’ve curated a list of top data analysis platforms for you in one place. Discover the unique features, pros, and cons of the analytics tools below.

1. Domo

Domo is a cloud-based analytics tool focusing on streamlining workflows and mobile features. Its high-powered, drag-and-drop extract, transform, and load (ETL) tool, programmatic management with API, and enterprise security features enhance your existing data warehouses and business intelligence tools.

With access to over 1,000 pre-built custom data connectors, 150 interactive charts, pre-built business apps, chat for instant collaboration, and push notifications, Domo makes it easy to understand and share data. This data analytics tool requires no coding, making it accessible to your entire organization.

2. Sisense

Sisense’s integrated data analytics platform balances everyday business use and more complex data analysis needs. It offers no-code, low-code, and pro-code options, so it’s accessible to all users, no matter their skill level. With AI-assisted analytics, predictive modeling, and customization tools, users can discover insights and empower forecasting in their data-driven decisions. 

See how Domo compares to Sisense

3. Google Analytics 

Analysts looking to gain insights from web traffic could benefit from using Google Analytics. This analytics tool features real-time reporting and dynamic acquisition and engagement reports to capture the most accurate picture of your audience. It also features predictive modeling language and drag-and-drop visualizations to help you better understand your engagement, advertising, and data collection techniques for further optimization. 

4. Tableau

Tableau’s analytics software is known for its data visualizations, scalability, and efficiency for business intelligence. Tableau is available in the cloud or on-premise and can connect with hundreds of data sources for easy data integration. Its interactive visualizations and dashboards are easy to use, featuring a drag-and-drop interface and no need for extensive coding skills or experience. However, not having a scripting layer means it’s less capable of pre-processing data or creating complex equations. 

See how Tableau compares to Domo

5. Talend

Talend is a Java-based  ETL tool and data integration platform that extracts, loads, and transforms data into databases for analysis or query creation. It’s capable of processing and integrating large data quantities. This analytics tool also features data management, a stich data loader, cloud storage, and a cloud pipeline designer to solve all your data management needs. Sharing data is simple with Talend’s comprehensive API delivery and data fabric services.  

6. Qlik

If you’re focusing on machine learning, consider Qlik. Its full range of augmented features, like automatic data preparation and creation, natural language interaction, artificial intelligence-generated reports and insights, and predictive analytics, provide your organization with actionable solutions.

This analytics platform combines all data sources into a single view to help users better understand and use data in real time. Qlik is available on-premise, the cloud, and as SaaS. 

See how Qlik compares to Domo.

7. Looker

Looker is part of the Google Cloud Platform. It easily integrates with other tools, offers over 50 SQL dialects, and has a powerful API for building custom applications from your data. Looker works on public clouds, multi-clouds, and hybrid environments for optimal flexibility. This tool is best suited for data exploration and visualization. It has a steeper learning curve than other analytics tools, so it may not be appropriate for those wanting organizational-wide use. 

See how Looker stacks up against Domo

8. Microsoft Power BI

Microsoft Power BI is commercial software offering a full suite of business analytics delivered through Microsoft’s Azure cloud platform. Data analysts can create custom, interactive visualizations and dashboards from numerous data sources. It also offers data prep and discovery within the same tool.

There’s not much of a learning curve with Power BI, and it’s even easier to use if you have experience with Excel. Free online tutorials are also available if your team requires training. With its mobile app, you can generate and share reports with others for easy collaboration. Working with too much data can slow down this platform, and data limits may require you to upgrade your plan. 

Learn how Power BI compares to Domo.

9. Klipfolio

Klipfolio’s data analytics software enables businesses to bring all their data together in one place so analysts can view real-time metrics and validate business decisions. This tool also tracks historical data to compare metrics over specific periods and discover trends. Klipfolio offers many third-party integrations, doesn’t require coding knowledge for use, and has dynamic reports, charts, and other visualizations. However, it does have limited API settings, which can impact efficiency and integration. 

Check out this comparison of Domo and Klipfolio.

10. SAP

SAP Analytics Cloud is an all-in-one cloud and data platform offering comprehensive analytics and business intelligence solutions. It comes with pre-built integration capability for other SAP products alongside other popular data tools like Salesforce, and Google BigQuery, providing seamless data integration and real-time insights. With its predictive analytics, planning capabilities, and advanced machine learning, SAP works well for businesses as a data analytics tool. The platform’s intuitive interface and drag-and-drop features make it accessible to users of all skill levels, while its robust security measures ensure data integrity and compliance with law or regulations governing data use.

11. Sisense

Sisense is a good combination of data analytics tools that work for both everyday business use and more complex data analysis needs. It offers no-code, low-code, and pro-code options, so it’s accessible to all users, no matter their skill level. Features include AI-assisted analytics, predictive modeling, and customization tools, allowing users to discover insights within their data. Sisense stands out from other tools on this list because of its ability to handle large datasets. It also includes many pre-built connectors allowing users to easily connect to some of their more popular tools.

12. ThoughtSpot

ThoughtSpot incorporates natural language processing within its data analytics platform, allowing users to ask questions about their data and analyze the results. ThoughtSpot integrates with various data sources, including Snowflake, Google BigQuery, and Microsoft Azure, enabling real-time data exploration. Its intuitive interface requires no technical expertise, making it accessible across the organization, though it lacks some of the advanced analytics features that other tools on this list have.

In an era where data is generated at unprecedented rates, choosing the right data analytics tool is essential for turning insights into actionable strategies. By understanding your specific needs and the various analytics options available, you can empower your organization to make informed decisions that drive growth and enhance competitiveness.

Data analytics tools FAQs

Have additional questions about data analytics or how to choose the best data analytics tool? We’re here with the answers.

What should I look for in a data analytics tool?

Many data analytics tools have similar features. When selecting an analytics software or platform for your business, here are some essential functions to look for:

  • User interface and visualization that supports non-technical users so your entire organization can understand and benefit
  • Advanced analytics tools that can identify patterns or trends in your data and help predict future outcomes
  • Integration with existing systems, third-party data, and complex data onto a single dashboard
  • The ability to customize the analytics tool
  • Flexibility and scalability that offer services to match your needs now and for future growth
  • The security features of the platform to ensure your organization’s information will be secure

What does data analytics software do?

Data analytics software helps companies collect, structure, and analyze data from numerous sources. Doing so can help business professionals identify trends or patterns, get to the root of an issue, predict outcomes, and develop insights for better decision-making. 

What software can I use for data analysis?

Numerous software options conduct data analysis, including more traditional methods like Microsoft Excel and modern cloud-based tools like Domo. A cloud-based data analytics tool may be easier to integrate, more customizable, and accessible for your entire organization to understand and use.

What is the best tool for analytics?

The best analytics tool has all the essential features your business needs. Key factors to consider when making this decision include:

  • Data volume
  • Data complexity
  • Type of analysis you want to conduct
  • The expertise of your team

What are the five types of data analytics?

The five types of data analytics are: descriptive analytics, diagnostic analytics, predictive analytics, prescriptive analytics, and cognitive analytics. 

Check out some related resources:

10 Data Visualization Tools for 2025

10 Data Governance Tools to Consider in 2025

Enterprise AI: What It Is, How To Implement, Examples

Try Domo for yourself. Completely free.

Domo transforms the way these companies manage business.