12 Embedded Analytics Tools for 2025
Embedded analytics tools are pivotal in the realm of data-driven decision-making. They offer organizations a seamless way to integrate data analysis directly into their existing applications and workflows. These tools empower users to access, analyze, and visualize data within the context of their daily operations—without needing to switch to an external analytics platform. As a result, businesses can harness the power of data more effectively, driving better insights and informed decisions.
Embedded analytics tools have grown significantly in recent years, with industry reports reflecting their increasing adoption across various sectors. Organizations today recognize the value of embedding analytics capabilities into their software applications;it not only enhances the user experience but also improves productivity and competitiveness. This trend has been particularly prominent in sectors like finance, healthcare, and e-commerce, where real-time data-driven insights are critical for success.
The history of embedded analytics tools can be traced back to the early 2000s, when the need for more streamlined and user-friendly data analysis became apparent. Over time, these tools have evolved to offer sophisticated features, customizable dashboards, and enhanced security measures. Today, they play a pivotal role in driving data-driven decision-making, offering a versatile solution for organizations seeking to make the most of their data assets. In the following paragraphs, we will delve deeper into the multifaceted world of embedded analytics tools, exploring their benefits, applications, and key considerations for implementation.
How to choose the best embedded analytics tool
Embedded analytics tools come in various forms to cater to different organizational needs and user preferences. The two primary types of embedded analytics tools are:
- Self-service embedded analytics: Self-service embedded analytics tools are designed to empower end-users, such as business analysts and non-technical staff, to explore and analyze data independently. These tools often feature user-friendly interfaces with drag-and-drop functionality, pre-built templates, and easy-to-use visualization options. Self-service embedded analytics tools are ideal for organizations aiming to democratize data access and analysis, allowing users to create their reports and dashboards without heavy reliance on IT or data professionals. This approach can boost productivity, as it reduces the time it takes to generate insights and make data-driven decisions.
- Developer-centric embedded analytics: Developer-centric embedded analytics tools are geared towards software developers and IT teams responsible for integrating analytics features into applications or products. These tools provide extensive customization options, APIs, and SDKs (software development kits) to enable developers to embed analytics seamlessly into their applications. Developer-centric tools often offer advanced capabilities for data modeling, security, and scalability, allowing organizations to create highly tailored and branded analytics experiences for their users. While these tools may require a higher level of technical expertise to implement, they provide greater flexibility in terms of design and functionality.
The choice between self-service and developer-centric embedded analytics tools depends on an organization’s specific requirements, the technical skills of its users, and the level of customization needed for embedding analytics seamlessly into their applications. Each type has its unique strengths and can play a crucial role in enabling data-driven decision-making within different contexts.
Choosing the right embedded analytics tool is a critical decision for organizations looking to integrate data-driven insights seamlessly into their applications and workflows. Here are some key considerations to help you make an informed choice:
- Assess your requirements: Start by identifying your organization’s specific needs and goals for embedded analytics. Consider factors such as the technical expertise of your users, the level of customization required, your data sources’ complexity, and your budget constraints. If you have a non-technical user base, prioritize tools with user-friendly interfaces and self-service capabilities. For developers, look for tools with extensive customization options and developer-friendly features.
- Evaluate integration capabilities: Ensure that the embedded analytics tool can integrate seamlessly with your existing applications and data sources. Check for compatibility with your programming languages, databases, and APIs. Look for tools that offer RESTful APIs and SDKs, as they simplify the integration process. Additionally, consider whether the tool provides white-labeling options, allowing you to brand the embedded analytics experience to match your application’s look and feel.
- Consider scalability and performance: As your organization grows, so will your data requirements. Choose an embedded analytics tool that can scale with your needs and handle large data sets efficiently. Evaluate the tool’s performance, especially with real-time data updates and concurrent users. Ensure that it offers features like load balancing and caching to maintain responsiveness under heavy usage. Scalability is crucial to avoid disruptions as your user base expands.
- Review data security and compliance: Data security and compliance should be top priorities when selecting an embedded analytics tool. Ensure that the tool provides robust security features, including encryption, role-based access control, and data masking. Evaluate its compliance with industry standards and regulations, such as GDPR or HIPAA, if applicable to your business. Additionally, consider whether the tool supports auditing and monitoring to track user activity and maintain data integrity.
- Budget and total cost of ownership (TCO): Understand the pricing structure of the embedded analytics tool, including licensing fees, maintenance costs, and any additional charges for advanced features. Compare the TCO of different tools over time to assess their long-term affordability. Keep in mind that while some open-source options may seem cost-effective initially, they may require more development effort and support costs in the long run. Balance your budget constraints with the tool’s capabilities and potential ROI.
By carefully considering these factors and conducting thorough research, you can make an informed decision when choosing an embedded analytics tool that best suits your organization’s unique requirements and objectives. Let’s take a look at some of the top tools currently available to support your embedded analytics needs.
12 top embedded analytics tools
1. Domo
Domo’s embedded analytics features have a robust suite of capabilities. It offers customizable dashboards, real-time data updates, and advanced security measures, enabling organizations to effortlessly integrate data-driven insights into their applications, partner’s programs, and workflows. Domo’s advantage lies in its user-friendly interface, allowing non-technical users to intuitively create embedded analytics dashboards and for other users to find quick insights. These features, combined with its easy-to-build and deploy custom data apps, set Domo apart from competitors in the embedded analytics space, making it the preferred solution for businesses seeking seamless integration of analytics into their operations.
Pros: User-friendly interface, robust data integration, wide range of data connectors.
Cons: Can be costly for smaller businesses; may require training for advanced features.
2. Tableau
Tableau provides powerful features that facilitate the seamless integration of data analysis into a variety of applications. Its notable capabilities include interactive data visualization, drag-and-drop functionality, and robust data modeling. These features empower organizations to deliver data-driven insights within their existing software environments, enhancing decision-making and user experiences. Tableau’s emphasis on interactive visualization sets it apart from competitors, making it an excellent choice for businesses looking to incorporate dynamic analytics into their applications.
Pros: High-quality visualizations, strong community support, extensive customization options.
Cons: Steeper learning curve for beginners; cost may be a barrier for some organizations.
See how Domo compares head-to-head with Tableau.
3. Looker
Looker, owned by Google, offers embedded analytics features designed to streamline the integration of data exploration, visualization, and reporting into applications and workflows—especially within the Google product suite. With robust data exploration tools, data modeling capabilities, and embedded reporting, Looker enables organizations to provide users with customizable, data-driven insights seamlessly within their existing software environments. This emphasis on flexibility and data-driven decision-making distinguishes Looker and positions it for businesses seeking to enhance productivity and decision-making through embedded analytics.
Pros: Data-driven decision support, strong data governance features, scalable architecture.
Cons: Complex setup for some users, requires SQL proficiency.
See how Domo comes out in comparison with Looker.
4. Power BI
Power BI, owned by Microsoft, encourages users to utilize embedded analytics to share information quickly and more widely. Power BI’s embedded analytics are based on Secure Embed, a no-code way to easily add reports into a web application. Power BI has features that support embedding analytics and data within and outside your organization, ensuring your data is available and up to date, while maintaining secure access to the data as needed.
Pros: Advanced embedding features, robust integration with Microsoft tools.
Cons: Limited embedding features for outside of your organization.
See how Domo comes out in comparison with Looker.
5. Sisense
Sisense provides a robust embedded analytics platform with embeddable widgets, a single-stack architecture, and data mashup capabilities. These embedded analytics features allow for the seamless integration of data-driven insights into a company’s products and services, empowering organizations with real-time, interactive analytics. When comparing Sisense to other competitor’s embedded analytics features, Sisense’s single-stack architecture and focus on embedding analytics into products give it an edge in terms of ease of integration. But other tools offer more visualization and powerful analytic engines behind their embedded analytics offerings.
Pros: Easy-to-use interface, quick deployment, support for large data sets.
Cons: May require additional investments for advanced features; limited self-serve capabilities.
6. Qlik
Qlik offers embedded analytics solutions featuring interactive dashboards and reports, with key features like an associative data model, in-memory data processing, and responsive design. Qlik’s embedded analytics tools support the integration of dynamic and user-friendly data-driven insights directly into end-user applications. Qlik’s associative data model allows for flexible and intuitive data exploration, even through embedded features. However, Qlik is limited in additional data features when compared to other tools on this list, especially Domo, which has a far broader range of capabilities within its embedded analytics capabilities.
Pros: Excellent data exploration capabilities, strong ad-hoc reporting, responsive design.
Cons: Requires specialized skills for development, licensing costs.
See how Domo works in comparison to Qlik.
7. Logi Analytics
Logi Analytics, owned by insightsoftware, provides a flexible development platform for embedding analytics within applications. Their embedded analytics tools offer extensive customization, easily reusable components, and white-labeling options, enabling businesses to create tailored analytics experiences that seamlessly blend with the application’s aesthetics. While Logi Analytics touts the white-labeling feature as one of the embedded analytics features, it’s not true embedding, especially when compared to the direct integration other competitors on this list offer. However, businesses can still benefit from the ability to integrate powerful analytics capabilities while maintaining a consistent and customized user interface.
Pros: Highly customizable, seamless integration, good support for original equipment manufacturers.
Cons: Can be complex to configure; limited data preparation tools.
8. MicroStrategy
MicroStrategy offers enterprise-grade embedded analytics solutions designed to seamlessly integrate analytics and data-driven insights into various applications. This is backed by their ability to provide robust and scalable analytics capabilities. With tools like mobile support and strong data governance, MicroStrategy ensures organizations have accessible and reliable insights across platforms through their embedded dashboards and supporting analytics.
Pros: Scalable architecture, strong mobile capabilities, robust data security.
Cons: Learning curve; potential for high implementation costs.
9. TIBCO Jaspersoft
TIBCO Japersoft provides embedded reporting and analytics solutions with critical business features like ad-hoc reporting, interactive dashboards, and open-source options. These provide developers with flexibility and scalability for embedding reports and dashboards into applications. However, when compared to others on this list, like Tableau or Domo’s embedded analytics features, TIBCO Jaspersoft may not be as strong in terms of user-friendliness and ease of integration. While other competitors excel in providing more intuitive and visually appealing interactive data visualization, TIBCO Jaspersoft does excel in the flexibility that advanced users can create through their open-source integration options.
Pros: Open-source version available, flexible reporting, scalable architecture.
Cons: Limited advanced analytics features; may require development effort.
10. Yellowfin
Yellowfin offers embedded analytics solutions that emphasize collaborative analytics, storytelling, and robust data governance. With these embedded analytics features, businesses can enhance their applications with interactive and collaborative, data-driven experiences while ensuring data quality, security, and compliance. These features make Yellowfin a compelling choice for organizations seeking to embed analytics and foster collaboration and data-driven decision-making within their applications.
Pros: Intuitive interface, excellent collaboration features, strong data governance.
Cons: Limited advanced analytics; potentially higher pricing for some features.
11. Birst
Birst delivers dynamic embedded analytics tools through its cloud-based platform. This cloud-based architecture offers the flexibility and scalability necessary for today’s data analytics and business intelligence support. Birst includes ad-hoc analysis capabilities within its embedded analytics features and has a wide range of data connectors, allowing businesses to leverage data from various sources to make informed decisions.
Pros: Scalable cloud solution, intuitive interface, good for multi-tenant scenarios.
Cons: Complex setup for extensive data integrations; learning curve for advanced features.
12. Thoughtspot
Thoughtspot touts embedded data analytics as one of its core features. It provides searchable data within the applications you use every day, and excels in data consolidation, making it easy to gather and centralize information from multiple sources. With a user-friendly drag-and-drop dashboard builder and automated reporting capabilities, Thoughtspot allows users to embed those in other applications so users can access data right within their workflows. However, while Thoughtspot empowers businesses to create compelling visualizations and streamline reporting processes, it ultimately doesn’t offer as many embedded analytics features as other tools on this list.
Pros: User-friendly, automation capabilities, extensive data source connectors.
Cons: Limited advanced analytics; may require development for complex customization.
No matter which product you choose, embedded analytics tools are revolutionizing the way organizations leverage data, placing actionable insights at the fingertips of users within their existing applications and right within their workflow. This integration streamlines workflows, enhances decision-making, and ultimately drives better business outcomes.
With Domo, organizations can not only embed analytics seamlessly but also access a wide array of features, including customizable dashboards, real-time data updates, and advanced security measures. By embracing Domo’s embedded analytics capabilities, businesses can empower their teams to harness the full potential of data, ensuring a competitive edge in today’s data-centric landscape.
Embedded analytics tools FAQs
Have additional questions about embedded analytics tools or how to choose the best embedded analytics platform? We’re here with answers.
What is an example of embedded analytics?
An example of embedded analytics is a business intelligence dashboard integrated directly into a company’s customer relationship management (CRM) software. In this scenario, users can access interactive charts and graphs displaying customer data and sales trends without leaving the CRM interface. This embedded analytics solution empowers sales teams to make data-driven decisions seamlessly within their familiar workflow.
What is the embedded reporting tool?
An embedded reporting tool is a software component integrated into another application, such as a business application or a website, to provide users with the ability to generate and view reports directly within that application. It allows users to access and analyze data without needing to switch to a separate reporting tool or interface. Embedded reporting tools often come with features for designing, customizing, and sharing reports, making it easier for businesses to provide data-driven insights to their users within their existing applications.
What are the benefits of using embedded analytics?
Embedded analytics offers several benefits, making it a valuable tool in the world of data analysis. First, it enhances decision-making by providing real-time data and insights within existing applications, enabling users to make informed choices swiftly. This integration also improves user experiences by eliminating the need for separate tools, increasing productivity. Additionally, embedded analytics allows for customization, scalability, and enhanced data security, making it a cost-effective and competitive advantage for organizations.
What is the difference between traditional analytics and embedded analytics?
Embedded analytics differs from traditional analytics in that it seamlessly integrates data analysis tools and features within existing applications, allowing users to access and analyze data without leaving their familiar workflow. Traditional analytics, on the other hand, require users to navigate to a separate analytics platform or tool, which can disrupt their workflow and necessitate additional training. This integration of analytics directly into the application enhances user experience, efficiency, and decision-making.