To understand Embedded analytics, we must first understand what data analytics is. Data Analytics is the scientific process of analyzing raw data and drawing out meaningful patterns and information from it. Data analytics techniques can reveal trends and metrics that would otherwise be lost in the mass of information. This information can then be used to optimize processes to increase the overall efficiency of a business or system.
What is Embedded Analytics?
Now that you have a better understanding of data analytics, we can now try to understand Embedded Analytics. As the name suggests Embedded Analytics is the integration of analytics into a different business application, websites portals, etc. so that users can seamlessly access and visualize their data in their own business environment making it easier for them to understand and make better and faster decisions in their business.
The analytics platform that is embedded into a software application may be unrecognizable to the end-user as a separate piece of software. This is called white-labeling – where the analytics platform is completely rebranded to blend in with the look and feel of the rest of the application into which it is embedded. This allows enterprise applications to market the analytics as their own.
Why Embedded Analytics?
- Achieves better time to value
With embedded analytics, there is no need for creating an analytics solution from scratch. It can be integrated into the application and rebranded using white-labeling (link to white labeling page). There is no need for an intermediary BI solution to view the visualization of your data since it can be incorporated into your site. This in turn helps in reducing costs since there is no middleman involved.
- An additional source of Revenue
The most valuable aspect and use case of embedded analytics is its ability to help you design new business models, that monetize the data that you already have, to create a new revenue stream. Displaying additional information through visualization by charging a premium is an example of earning additional revenue.
- Predictive models and Trends in your business application
Analytics must provide informative and diagnostic data of a webpage. New technologies like ML and AL are used in making prediction models which are used in BI tools and other ML applications. With the help of Embedded analytics, it is possible to get these features from BI tools to your web application through embedded analytics. Predictive models and trends help businesses understand different questions like:
“What is the current state of the business? “
“Where are the ups and downs in sales? “
“What is the trend in sales and profits? “
- Get to market faster
The Customer doesn’t have to build the product from scratch. He can tune and adjust the settings the way he wants them.
- Save on costs to build and maintain
The cost of development can be minimized by avoiding a full-scale analytical solution that would require expensive resources.
Use cases for Embedded analytics can be found in every industry. Embedded Analytics find their applications in various domains like E-Commerce Dashboards, Web Portals, Conversation websites, and Business applications.
Why should you choose to embed Sisense analytics in your business model?
- Seamlessly integration with your current interface and branding
- Manage data, reporting, and visualization
- Integrate SSO and Active Directory
- Govern user and data security
- Support high availability and resource scaling
Types of Embedding
Typically, there are three types of Embedding: –
- IFrame Embedding: This is the easiest way to get a dashboard from the UI. Embedding is done by URL where UI is linked to your website using the iframe tag.
Thinking of embedding analytics into your websites and applications? then you are in the right place, get in touch with us and we will help you create a customized solution for your analytics needs and reap the benefits in a short time! Liked this article? Feel free to share this article.