In our recent eBook, Self-Service Can Be Embedded Too, we dive into the need for applications to be data driven, and we describe the various BI & analytics capabilities that can be embedded into your application.
Read on to get a short excerpt of what’s inside!
Better Outcomes with Data Driven Apps
With an integrated approach to analytics, end users can focus on working within one application rather than two and benefit from contextualized analytics.
This is the hallmark benefit of embedded analytics as it provides a clean, seamless user experience for supporting two platforms in one. Users can navigate the application without second guessing if the analytics was bought and can perform the same workflows but with data insights.
Embedding Self-Service and Visualizations
In this section, we discuss different strategies to embedding analytics in your application.
We find that many organizations elect to embed different features in different ways. For example, reporting can sometimes be a separate module on your application or visualizations embedded directly within a page or workflow.
It is up to your organization what features are critical to being embedded where, and to find a vendor that best supports that embedding strategy.
Embedded Data Integration
For organizations with many data sources or keen on allowing end users to connect and mash up any data source, self-service data integration should be a goal. The ability to mash up organizational data with external data allows for greater insights.
Looking for modern embedded frameworks that have flexible data integration service is key. Look for access to a wide variety of data sources with the flexibility of access, integration capabilities, and discovery tools.
The Core Technical Requirements
When evaluating embedded BI solutions, look to the solution’s core architecture. Ensure it offers a rich set of APIs, endless configuration options, and architecture that will support you as a customer for a life time.
Make sure you are not purchasing a toolkit or a set of libraries. Flexibility is key. Having ownership of their visualizations, and design to fit any infrastructure, for example, allows the product to move where your product goes or fulfill feature requests that may be critical to your application.
In sum, the back-end of an embedded BI product is supremely important to monetizing data. Not only is it important to evaluate for the here and now, but also future proofing the analytics that will go into your application is important. Product roadmaps and core architecture can tell you how flexible a solution is in fitting both your current and future needs.
Read the full eBook here, and get the full scoop.