Embedding analytics puts them in the hands of as many teams as possible easily. As part of data-as-a-service, companies are implementing embedded BI analytics and yielding great ROI. Most of the time, the business model will have requirements like these for BI vendors:
- How can I allow my company’s external users to access the dashboards created?
- How can I provide the visual analytics features that my customers want?
- Analytics in my product—do I make or buy?
- How do I get to the analytics market quickly with an integrated partner incurring less cost?
Embedded BI is the answer. This blog will go through all these questions. And being an important part of the business ecosystem, you can see embedding is present in:
- Web pages and applications: Portals, CRM tools, chatbots, and even voice assistants like Alexa.
- Industry/Department: CRM, IT, marketing and sales, finance, production, supply chain, retail, HR.
- Deployment Model: Enterprises and SaaS.
Why embedded BI?
A perfect dashboard can take full advantage of your data. Meanwhile, embedded analytics can drive great traffic to that dashboard. The major forces driving the embedded analytics market are below,
- The rise in data-driven organizations,
- Higher adoption of self-service analytics,
- Increasing demand to integrate analytics with business applications.
Products providing one or more software services will have analytics or dashboards as part of their application. This lets their users analyze their own data generated when they use that product. It allows them to gain business insights while using that product. They don’t want their users to switch to another application for analytics purposes. For this, they need to determine whether to make or buy an analytics and BI solution for their product. When they do buy and embed an analytics and BI solution in their product, they don’t need to worry about maintaining it as well.
Such use cases will be generally achieved via OEM deployment, i.e., white-labeling and rebranding. For these second-level customers, resources like databases, servers, and application domains act behind embedding. These resources will be either shared or dedicated to specific tenants based on the requirement. The BI vendors usually charge with terms like tenant, agent, partner, or reseller. The license to buy depends on multiple factors, including the number of users, number of dashboards, and your SLA with your external users.
So, what is embedded BI?
Embedded BI is the integration of dashboards into business applications. An external user can play with the dashboards without being involved with the BI tool that created them.
White-labeling allows companies to maintain their brands by replacing the BI tool’s name with their company name. Similarly, it allows having their own domain name on the website.
Users can interact with dashboards by filtering data, commenting about a metric displayed, etc. This will give users the feeling that it is part of that original application and makes its separate nature invisible.
In general, the feature set of embedded analytics can’t be limited to a level. It depends on the use case, and most of the time, customers expect a customized solution. The best vendors are always ready to provide customized, relevant solutions with deep embedding support.
And please note that embedded BI is not required if the requirement is simple. For e.g.
- A dashboard that can be viewed by anyone. (Public dashboards).
- A dashboard available as an image, PDF, or Excel file.
Security in embedded BI
While embedding dashboards, privacy and security concerns should be considered. Certainly, SSO (single sign-on) or login authentication schemes like OAuth are used in general to access a dashboard securely. Beyond that, controlled data access with permission enabled at user and row levels also important.
E.g., a retail store sales dashboard can tell you about the overall sales performance of all the stores in a city. The same dashboard can be sliced to show one store alone, accessible to only that store’s manager, by enabling user-based access to it. This store manager will not be able to see the combined sales metrics of all the stores in the city. Only the city manager will be able to investigate that.
Other notable security factors are:
- You should constantly monitor public URLs (dashboards) and disable them if they are not used.
- Web-based dashboard pages should be compliant with the existing security model of the web app in which that dashboard is going to embed.
- You should allow integration for custom authentication needs, like integration with Active Directory. This allows reusing of existing user roles and rights.
How is embedded BI implemented?
Data analytics is not an expensive or difficult-to-implement commodity like before, and it is no longer only for data analysts and business analysts. With the technical explosion, it is now easily accessible by any company of any size. Embedded BI analytics help decision-makers at any level make decisions quickly, reducing time wasted due to context-switching between applications.