Embedded analytics is a game changer in the realm of business intelligence. Unlike traditional analytics that require users to switch between multiple platforms, embedded analytics integrates powerful data analysis capabilities directly into existing applications. This seamless integration not only enhances the user experience but also ensures that critical insights are available precisely at the right place and right time. With embedded analytics, users can make data-driven decisions faster, improve operational efficiency, and drive business growth.
Before embedded analytics, the BI solutions faced a significant hurdle in accessing and utilizing data effectively. Critical metrics were spread across sources, requiring users to manually gather and consolidate information from multiple sources. This fragmented setup led to delays, inconsistent reporting, and a limited view of operational insights, making it challenging for teams to make timely and data-driven decisions. The lack of integrated analytics also affected efficiency, as users had to navigate multiple applications, each with its own login requirements, interfaces, and data constraints. Additionally, there was the challenge of securing sensitive information and ensuring that only the right users had access to specific data, which further complicated the data management process.
The best way to explain embedded analytics is like driving a car where all the crucial information such as speed, RPM, temperature, fuel, etc., are right in front of you, allowing you to stay focused on the road without getting distracted. This analogy captures how embedded analytics integrates all necessary data insights directly into the user interface, ensuring seamless access to information without disrupting the workflow.
In this blog, we will start with one of the success stories with the WellSky Hospice & Palliative Care (H&P) application to highlight the impact of embedded analytics and then move on to explore the advantages and disadvantages of the same, backed by statistics, demonstrating how it can enhance the value and quality of your application.
H&P Application
In our recent project with H&P, we successfully embedded over eight dashboards into the application. This integration has significantly improved operational efficiency and data accessibility. To ensure data security and appropriate access, we implemented Row-Level Security (RLS) using Web Access Token. This approach controls user access to specific subsets of data, ensuring that sensitive information remains secure. For instance, a department head can view only the total patient visits for their department, while organization administrators can access comprehensive data across all departments. This granular control over data visibility guarantees that users have access to relevant information without compromising sensitive data.
Here is what our clients have to say:
- "Much quicker to return results."
- "The updated dashboards are not only visually appealing but also very functional. They provide a comprehensive view of the key metrics, including patient visits, referrals, and care outcomes."
- "The dashboards run a lot faster and are easier to filter and sort."
- "The embedded solution is user friendly and has integrated seamlessly into our existing workflows. The overall experience is much more cohesive, and the information we need is right at our fingertips. "
Advantages of Embedded Analytics
- Improved decision making: Users can make informed decisions quickly with data insights directly within their workflow.
- Increased user engagement: Integrating analytics within an application keeps users engaged, reducing the need to switch between multiple windows.
- Customization: Tailored dashboards and reports can be designed to meet specific user needs, enhancing the overall user experience.
- Cost efficiency: Reduces the need for separate analytics tools, thereby saving costs on user licensing and training.
- Enhanced value proposition: Offers a competitive edge by providing users with advanced analytics capabilities as part of the core application.
Disadvantages of Embedded Analytics
- Complex integration: Embedding analytics can be technically challenging and may require additional development resources.
- Performance issues: Real-time analytics can put a strain on system performance if not optimized properly.
- Data security: Ensuring data security and privacy can be more complex, especially with sensitive or multi-tenant data sources.
Statistics Highlighting the Impact of Embedded Analytics
- Increased efficiency: Organizations using embedded analytics report a 30% reduction in time spent on data analysis.
- Higher user adoption: Applications with embedded analytics see a 20% increase in user engagement.
- Improved accuracy: Real-time analytics improve decision making accuracy by up to 25%.
Conclusion
Embedded analytics brings significant value to applications by improving decision making, user engagement, and operational efficiency. Despite some challenges, the benefits far outweigh the drawbacks, especially with robust security measures like RLS. Our experience with H&P demonstrates the transformative impact of integrating analytics into business applications, making data driven insights readily accessible and actionable for all users. Additionally, we are striving to embed valuable BI analytics and reports into WellSky applications, further enhancing their functionality and user experience.
References:
- ThoughtSpot on Embedded Analytics:
https://www.thoughtspot.com/data-trends/embedded-analytics
- LogRocket Blog on Embedded Analytics:
https://blog.logrocket.com/product-management/embedded-analytics-definition-overview/
- Reveal BI on Embedded Analytics Benefits:
https://www.revealbi.io/blog/benefits-of-embedded-analytics
- NetSuite on Embedded Analytics:
https://www.netsuite.com/portal/resource/articles/data-warehouse/embedded-analytics.shtml
- HackerNoon on Embedded Analytics:
https://hackernoon.com/understanding-embedded-analytics-definition-benefits-and-use-cases
