Embedded Analytics
What are embedded analytics?
Embedded analytics refers to the integration of data analytics capabilities, such as dashboards, reports, and data visualizations, directly into applications, products, or workflows. Unlike traditional business intelligence (BI) tools that require users to switch to separate platforms, embedded analytics keeps insights within the context of the tools people already use, enhancing decision-making at the moment of action.
Why do embedded analytics matter?
Modern users expect data to be available when and where they need it. Embedded analytics empowers product teams to deliver on this expectation by putting insights at the fingertips of end-users, without requiring them to leave the application. This improves user experience, increases product stickiness, and accelerates time-to-value. For internal tools, it boosts operational efficiency by enabling faster, more informed decisions. For customer-facing apps, it unlocks new value and revenue streams by turning analytics into a product differentiator.
How do embedded analytics work?
At its core, embedded analytics relies on APIs, SDKs, and flexible front-end components to integrate visualizations and data interactions into digital experiences. Advanced platforms like Sisense offer no-code, low-code, and pro-code tools to support creators across the technical spectrum—from developers embedding analytics into custom UIs to product managers configuring self-service dashboards. GenAI-powered features like natural language queries and automated insights make analytics more accessible to all users.
- Product teams embed dashboards and KPIs into their applications to drive user engagement and satisfaction.
- Developers integrate analytics features using JavaScript and frameworks like React, Angular, or Vue for full control and customization.
- Data analysts design interactive visualizations that deliver insights in context, without requiring engineering support.
- Executives and customers get real-time access to insights embedded in the tools they use every day, reducing friction and accelerating decisions.
Benefits of embedded analytics
- Increases user engagement by delivering data in context
- Enhances product value with data-driven features
- Reduces time spent switching between tools
- Empowers both technical and non-technical users
- Accelerates innovation through low-code customization
- Supports scalable, secure, and branded analytics experiences
Embedded analytics vs. traditional BI
Traditional BI tools often require users to log into separate systems to analyze data. Embedded analytics, on the other hand, brings data to the user, within their existing workflows. It’s the difference between asking users to find insights and delivering insights where they’re already working.
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