Embedded Analytics in Business Intelligence – Overview

According to Gartner, “…a digital workplace capability where data analysis occurs within a user’s natural workflow, without toggling to another application.”

What is Embedded Analytics?

Embedded analytics means the integration of analytical capabilities and data visualizations into a software application. The end-user can analyze the data held within the software application. Here, the analytics platform is embedded by embedding real-time reports and dashboards.

The end-user can use this analysis to identify and mitigate issues and maximize opportunities. Embedded analytics tools also allow software companies to fully acquire and integrate an analytics platform into their SaaS product. 

Embedded analytics combines data from various sources to create comprehensive charts and dashboards. Data integration is followed by data transformation, modeling, and visualization. Embedding analytics into a business process provides end-users with quick and easy access to data visualizations as part of their daily tasks.

The main difference is that embedded analytics is a software solution integrated into another application or web portal rather than a standalone solution. This integration could be purely aesthetic, or it could go much deeper into the foundations of the two tools.

End-users of embedded analytics solutions (business managers and specialists) may be unaware that they are using analytics in their business processes. Whereas dashboards and visualizations are embedded into another application or web portal — they see it all as one tool.

Who Cares About Embedded Analytics?

While embedded analytics has a wide range of applications, there are essentially two main reasons for companies to pursue it:

  • Data-driven businesses: This type of company wants to create a data culture within its organization. It also encourages internal teams and external partners to be data-driven by providing them daily access to data (and its benefits).
  • SaaS (Software as a Service) companies: These companies enhance their product’s capabilities by integrating them with an analytics platform. Also, it helps in effectively merging the two products into a single one.

Embedded Analytics: What to Look for?

When considering other vendors as part of the process of acquiring a solution, you will undoubtedly have a long list of criteria in mind:

  • Build or buy: For software product vendors looking to embed analytics into their SaaS product, they’ll face one classic inquiry: “Should we build our solution or purchase one from a specialized data analytics provider?”
  • Scalability: Will the solution scale with your future expansion plans?
  • Drag-and-drop visualization for self-service: Is it possible for my employees or customers’ end-users to create their analytics visualizations or dashboards without prior technical knowledge?
  • Privacy and security: What data is accessible, and how is data from different teams or customers separated?
  • Pricing predictability: Is the pricing model transparent, and how does it affect current and future profitability?

How to Embed Analytics?

There are two primary methods for integrating your analytics. These are:

  • Basic iFrame embedding: This enables the simple embedding of customized, preset visualizations, dashboards, or even a user-friendly, self-service analytics interface with single sign-on. You can also consider it as a copy-paste function.
  • APIs, SDKs, and Javascript libraries for advanced embedding: This allows you to customize anything as React, Angular, and Vue components. Also, you can embed anything, from customized interfaces to fully interactive dashboards. Even it creates an entire analytics interface that isn’t based on traditional charts and graphs. 

5 Advantages of Incorporating Analytics into your Software Application


Analytics embedded in your enterprise software application can significantly benefit your product. Embedding analytics also provides business opportunities ranging from increasing user engagement to providing new revenue channels to decreasing client churn.


Five of the most crucial reasons for incorporating analytics into your app as a software developer

1. Long-term competitive advantage over your competitors

You will not compete with your rivals if you do not have modern analytics embedded within your application that provides actionable insights. Clients have come to expect analytics across the board.

Hence, organizations want to use analytics to unlock the wealth of data locked in the software applications they buy. As a result, more data is being produced than ever before.

By incorporating the right modern analytics platform, you give your end-users the ability to take advantage of new technology to get to the heart of data – insights quickly.

2. Ability to provide your customers with a fantastic analytical experience

You can deliver new capabilities to transform how your customers use your application when embedding a modern business intelligence platform.

They’ll be able to program their capabilities into dashboards, for example, or get instant, automated insights without manually grafting data together.

In a governed platform, they can collaborate on data and share insights. As a result, modern analytics provides a better user experience with improved UI and flexible design options.

3. Upsell opportunities provide additional revenue streams

You will be able to add revenue streams and upsell them due to the enormous value provided to your customers by modern analytics. The analytics module could (and should) be used to generate additional revenue.

Alternatively, you could include dashboards and embedded reports as standard in your application. Also, you can reserve automated insights as an upsell opportunity for your sales team.

4. Ability to quickly get to a competitive market

If you build your analytics capabilities, you will run into deployment issues, setbacks, and delays. If it takes more time to get to market, analytics will take more time to generate revenue.

But with the right analytics partner, you will be able to get to market fast. This in turn will help you remain competitive in the market. 

5. Allows putting concrete efforts into improving your core product

Instead of building it from scratch, embedding business intelligence and analytics allows your developers to focus on your core offering. 

Hence, by adding new features and integrating the latest technologies, you and your clients can get an ever-better product and experience. 

Standard Capabilities of Embedded Platforms

Some features are common across almost all platforms, regardless of how good they are. However, leading platforms will provide additional features such as automated options and AI capabilities.

Before you buy analytics, read up on the six most important things to know, but here’s a rundown of common features in embedded analytics platforms: 

1. Data Preparation

Organizations must have their data ready for analysis for any analytic project to succeed. Data preparation capabilities give you the BI tools to connect and extract data from multiple sources while also making data outputs accessible to end-users.

The software provider typically uses this capability to ensure that their customers have the most accurate, clean data to work within embedded analytics scenarios.

2. Data Dashboarding

A data dashboard is the most effective way to see multiple data reports in one place and take action. Also, dashboards generate multiple reports together so that your clients can get a complete picture of the company’s performance.

Modern dashboards even allow developers to code actions, such as order buttons, into dashboards, allowing users to complete their workflow without ever leaving the dashboard. Hence, embedded analytics platforms should also enable end-users to create their dashboards and customize the look and feel to match their brand.

3. Data Discovery

Your customers must explore their data, discover patterns and outliers, and share their findings with others to better understand their business. Data discovery capabilities in embedded analytics allow your clients to find insights in the data stored in the application.

Also, they share and disseminate those insights in a controlled manner. With the rise of augmented analytics, data discovery has become more automated. Machine learning algorithms can search for patterns in data indefinitely and notify relevant users when a statistically significant change occurs.

4. Interactive Reports

Interactive reports should be simple to create. End-users of this analytics may want to make their reports. Still, even if they don’t, they will want to drill into further detail. Also, they will visualize the data in tables, charts, and graphs, query it, and compare it with other data points.

More powerful interactive capabilities have been enabled by machine learning, such as clicking on a data point. Also, having it automatically explained through related data and natural language exclamation points. It also gives greater clarity on the data faster to take action sooner.

5. Mobile Reporting

Providing your customers with their dashboards and reports on mobile devices is critical in some industries. For example, seeing machine performance, downtime, and production rates via a tablet anywhere on the factory floor can be invaluable.

Furthermore, in highly reactive, fast-paced industries, receiving automated data discovery alerts on a mobile device can mean the difference between success and failure.

6. Easy Collaboration

Within the embedded analytics platform, governed collaboration over data insights and report creation saves your clients time and adds stickiness to your application.

Suppose your clients can collaborate where the data exists rather than copy and paste screenshots into emails and instant messaging platforms. In that case, they will remain on the platform longer, will have live visibility of their data, and can take action instantly.

The Future: Augmented Reality in Embedded Applications

As augmented analytics (the use of machine learning (ML) algorithms and artificial intelligence (AI) in analytics) becomes more popular. It also results in more automation than manual labor in traditional BI and analytics. If your software application includes analytics, this automation benefit has some great benefits for you and your clients.

Using augmented analytics, you can market an AI-enabled product and provide data insight and faster benefits to your customers. You can start integrating embedded analytics in your business application with Thinklytics. For details, connect with our expert analytics. 

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