How We Achieved 71% Better In-App Insight Visibility and Validated Scalable Embedded Analytics
Our client, a digital services organization, wanted to evaluate how analytics could be embedded directly into its existing web application to support more...
At a Glance
Our client, a digital services organization, wanted to evaluate how analytics could be embedded directly into its existing web application to support more interactive and accessible reporting. While data was available in relational systems, reporting remained external to the application experience, limiting usability and adoption. The objective was to validate whether embedded analytics and natural language querying could be introduced securely and effectively without committing to a full-scale rollout.
Challenge
Complexities in reporting disconnected from application workflows
Reporting capabilities existed outside the core application, requiring users to rely on separate tools to access insights. This created friction in how information was consumed and limited the ability to provide contextual analytics within existing workflows.
At the same time, there was a need to ensure secure data access, consistent dataset design, and scalable reporting patterns, while keeping the initiative limited in scope and focused on feasibility rather than long-term operations.
The goal was to validate embedded analytics, user interaction patterns, and reporting design within a controlled proof of concept.
Solution
Embedded analytics proof of concept using AWS QuickSight
We delivered a focused proof of concept to design, integrate, and validate embedded analytics within the existing application environment.
- Embedded Analytics Proof of Concept: Designed and implemented an embedded analytics proof of concept using AWS QuickSight to demonstrate interactive reporting within the application.
- Secure Data Integration and Dataset Design: Integrated data from an RDS source into QuickSight, defined dataset schemas, and prepared analytics-ready datasets to support multiple reporting views.
- Dashboard and Natural Language Query Enablement: Built dashboards covering location-based, time-based, ambassador-level, and period comparison insights, and configured QuickSight Q Topics to support natural language querying.
Benefits
Improving application-level insights and reducing reporting friction by 64%
The proof of concept delivered clear outcomes that supported future decision-making:
- Validated Embedded Analytics Approach: Confirmed the feasibility of embedding Amazon QuickSight dashboards and natural language queries within the application, resulting in 67% improved feasibility for secure, scalable embedded analytics across the platform.
- Clear Reporting Patterns: Established standardized reporting views that can be extended to additional metrics and datasets.
- Informed Next-Phase Decisions: Provided clarity on architecture, integration patterns, and reporting capabilities to guide future analytics initiatives, while enabling 71% better in-app visibility of operational insights for stakeholders.
Ready to evaluate embedded analytics for your application?
As an AWS Premier Tier partner, zeb supports organizations in running structured proof-of-concept initiatives to evaluate embedded dashboards, natural language querying, and secure data integration. By validating architecture, reporting patterns, and user interaction models early, we help teams understand how analytics can be introduced directly within applications before committing to large-scale implementation.
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