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The terms "embedded analytics" and "business intelligence" are sometimes used interchangeably, which actually makes sense. The end goal of both is to provide actionable insights to a group of users through data visualization. However, there are not that many similarities beyond this point.
Today, we'll show you the main differences between an embedded analytics solution and a traditional business intelligence (BI) tool and help you find out which one you need for your business.
What is an embedded analytics platform?
An embedded analytics solution is a piece of software that integrates analytics, reporting, and data visualization capabilities directly into another application, platform, or workflow. Instead of opening a dedicated tool for data analysis and visualization, users can access information directly in another app or platform without switching back and forth between tools.
Embedded analytics tools work by integrating dashboards, reports, and data visualizations into an application using APIs, SDKs, iFrames or Javascript for embedding. The data for the embedded dashboards is pulled from various sources, such as data warehouses, data lakes, CRMs, ERPs, SaaS apps and others.
Examples of embedded analytics software include Embeddable, Sisense, ThoughtSpot and others.
What is a business intelligence platform?
A business intelligence (BI) platform is a software solution that helps organizations collect, analyze, and visualize data to support strategic decision-making. Unlike embedded analytics, which integrates insights into existing applications, BI platforms are typically standalone tools where users can explore data, generate reports, and uncover trends to help with data driven decision making.
Notable examples of traditional BI solutions include Salesforce's Tableau, Microsoft Power BI, Looker and others. Note that these tools have their own versions of embedded BI software too.
For example, there is Looker for in-house dashboards, reporting and business processes, and Looker Embedded for embedding dashboards into existing systems such as apps or websites.
The key differences between embedded analytics and traditional business intelligence
Many traditional BI tools (e.g. Looker, Tableau, Microsoft Power BI) offer embedded analytics software as a portion of their product. However, there are distinct differences between traditional BI and embedded analytics.
The scope, definition and purpose
Business intelligence is a concept that includes data analysis, reporting, and visualization, typically within standalone BI platforms. For example, a business analyst logs into Power BI to get the sales forecast for the upcoming quarter based on past data.
On the other hand, embedded analytics tools enable you to integrate data visualizations directly into your applications, software, or workflows, allowing your customers to access insights without leaving your application. For example, when you log into Stripe and see a dashboard of your revenue & subscriptions. There is also a set of embedded analytics requirements a tool should meet to work well as a part of your tech stack.
The target audience
The primary audience for business intelligence tools is internal teams in businesses. For example, if a marketer wants to share the results of their newest paid ad campaign, they'll create a dashboard for the CMO and the rest of the executive team. Everyone can access the same dashboard with a link, based on data from the company data set.
On the other hand, embedded analytics tools are meant for businesses that have their own customers. For example, a SaaS sales platform wants to enable their customers to create and share dashboards about what is happening in their product. For example, a sales rep can generate a sales report in that SaaS app and share it with their manager.
The user experience
In traditional BI tools, because the data consumers are your internal team, the focus is on the data and not the UX. In other words, the dashboards, reports and their user experience are mainly basic. The main goal is to drive better business decisions internally.
One of the biggest advantages of embedding analytics into your app is how customizable everything is. Great embedded BI tools blend perfectly into existing business applications or websites. When the user clicks through on a dashboard or report, it feels like a native part of the platform. It loads quickly, it's easy to use and explore data, which is imperative for true data democratization.
Customization and integration
There is no need for major customization options with traditional business intelligence. As the dashboards are shared internally, the primary concern should be how to adjust the different visualization types to clearly portray the most relevant data.
Embedded analytics, on the other hand, requires extensive customization. The dashboards are frequently embedded into websites and apps with different methods such as iframes or SDK, so that the UX and UI match the rest of the platform.
This requires customization in colors, fonts, design elements, visualization types, widgets and their placement and much more.
Deployment and accessibility
Business intelligence tools are hosted in a centralized data platform, accessible via a dedicated BI tool. They can be based in the cloud or hosted locally on a server for businesses that need superior data security.
Embedded analytics dashboards are accessed within software applications via dashboards, widgets, or APIs. For example, logging into your e-banking app to see an overview of your spending and savings for the year.
Historical data vs. real time data
Typically, traditional BI tools don't require real-time data. When business users create dashboards and reports, they are based on historical data, e.g., for the week, month, or quarter. In other words, there is no urgency for dashboards that constantly update.
Data access needs for embedded analytics users are different. For example, a marketer looking into PPC reports needs timely data to make quick decisions.
Self service capabilities
Business intelligence tools typically offer self-service analytics but require users to build reports, dashboards, and queries. In other words, the data scientist in the team can prepare, structure and model the data but someone else typically has to build interactive visualizations that provide relevant business insights.
On the other hand, embedded analytics is designed to provide insights with minimal effort from the user, often in a simplified, automated manner. This means that anyone can open a report or dashboard and understand the data without having to build anything by themselves.
Choose embedded analytics if...
Here's how you'll know if you need an embedded dashboard with seamless integration to the rest of your product or website.
You have a SaaS platform with built-in reporting
Let's say you have a SaaS project management tool and you want to offer users real-time analytics on task completion rates, team productivity, and project progress, all without users leaving the app. Embedded analytics lets users access these insights directly within the software so they don't have to go to a third-party app.
You need customer-facing dashboards
Perhaps your team doesn't need dashboards, but your customers do. For example, an e-commerce platform wants to give its vendors a customer-facing dashboard that tracks sales performance, top-selling products, and revenue trends. Using embedded analytics lets vendors view and act on data without needing a separate BI tool.
You want to support operational efficiency and decision-making
Let's say you run a hospital and have an internal patient management system where doctors and nurses need real-time patient monitoring (vital signs, test results, and medication schedules). Embedded analytics provides real-time insights directly within the healthcare application, helping you save time and money, all the while staying compliant.
Choose business intelligence if...
And you might not need embedded analytics at all and you should use a dedicated BI tool instead. Here are some tell-tale signs all you need is BI.
You primarily need data insights for your in-house team
If you only need to analyze data internally and you don't have end-users or customers that need data insights, you're better off with a business intelligence tool. You can share dashboards internally with just a few clicks and your team can open them with a link and head straight to your BI tool.
You don't always need real-time insights
Data-driven businesses don't always need fresh, real-time data. Sometimes, all you need is historical data for the past month or quarter to make future predictions from complex data sets. If this is the case, any traditional BI tool will do the job.
User experience and customization are not a priority
If data is all that matters, then how you display it might not matter. You might not need beautiful, customized dashboards with tooltips and fast-loading widgets. Instead, you just need a simple and clear representation of relevant data, no extra bells and whistles.
You have an in-house team of data professionals
Embedded analytics is better suited to non technical users who can work on ready business data. On the other hand, in-house teams typically have teams of data scientists, engineers and other professionals who can model and clean the data and possibly even create dashboards and visualizations for other team members.
Conclusion
Business intelligence tools and embedded analytics are both relevant for today's businesses, but they serve two very different audiences. Traditional BI is here to stay, but modern embedded analytics are spreading like wildfire as more and more businesses realize the value of data-driven decision-making.
If you're considering building an embedded dashboard for your product, Embeddable is a superb choice. With a developer-friendly SDK, the ability to use any charting library you can, and a great selection of data sources, we can make your end-users and dev teams happy.
Sign up and get access to Embeddable today.