What are Embedded Analytics
Analytics that are integrated within an existing application, product, or service are referred to as “embedded analytics.” Within the BI and Analytics market, the term is widely associated with an approach that involves licensing third-party technologies to embed within a host product or service. Third-party vendors who have offerings in this area will typically describe them as “embedded BI,” or “embedded analytics” or even “embedded intelligence” software products.
Benefits of embedded analytics accrue to both product owners and end users of the product. Licensing embedded BI and analytics technology significantly reduces the resources required to develop and maintain these capabilities. The ability to focus more energy and mindshare upon core product or service capabilities is an important benefit of embedded analytics. Product owners can differentiate their offering through a richer, more robust analytics capability and achieve time-to-market advantages in the process. Valuable data sitting around on company servers could be monetized through better products and services utilizing an embedded analytics approach. With fewer components to install, configure, or update, embedded analytics also ease deployment issues for providers and end users.
Embedding not only minimizes training and learning costs, it offers superior usability by placing analytics where they can make the greatest impact, on the same screens where a user is already do their work and making decisions. Embedding analytics help users by letting them stay focused on the task at hand while boosting the effectiveness of their outcomes by providing data insights where and when they want them. The reduced learning curve for users of embedded BI provides greater efficiency. If a new application or service is being introduced, users do not have the additional burden of learning to use a separate analytics product. Users have access to analytics capabilities within the primary product and can make better decisions more quickly. For example, a doctor can make more informed treatment decisions if patient history analytics are available within the consultation application. A security auditor can prescribe a more effective plan for safeguarding data based on historical metrics on violations and breaches.
Some examples of applications using embedded BI include a CRM application with a full-featured reporting module for understanding the sales pipeline, fantasy sports research sites showing player statistics, , and consumer health apps with visualizations of recent activity collected from fitness trackers.. We are also beginning to see analytics embedded into physical machines and devices such as farm tractors and household electronics such as thermostats.