10 Embedded BI Features Every SaaS Apps Need (2024)

Imagine you’ve built an amazing SaaS app, something so slick and useful that customers are practically doing a happy dance whenever they log in. You’ve nailed the core functionality, the design’s on point, and even support tickets are few and far between. But then comes the request—no, the demand—from customers: “We want to see the data right here! Don’t make us export your data and hop over to Excel!”

You’re a developer; you know that adding analytics could be transformative. If users could see data insights right in your app—no separate dashboards, no back-and-forth to some other tool—it would make your app feel like a one-stop solution. More stickiness, more value, more time saved, and louder cha-ching! But building that dashboard or embedding BI? That’s a whole project of its own. It’s one thing to bring analytics into an app; it’s another to make sure it’s useful, secure, and intuitive.

So, here’s where Embedded Business Intelligence comes into play.

Instead of building that data magic from scratch, you can integrate a pre-built, flexible BI system that gives customers exactly what they’re asking for real insights, right inside your app. And the best part? You don’t have to reinvent the wheel on analytics. Your app stays in the spotlight, and the embedded BI tool works quietly in the background, serving up custom dashboards, data visualizations, and real-time updates.

This article is your map to mastering Embedded BI tools. We’ll break down what makes it tick, the features that keep it running smoothly, and the non-negotiables you need to have before embedding any BI tool into your SaaS.

Core Features of Embedded BI

When it comes to embedding BI in your app, it’s not just about slapping a dashboard in there and calling it a day. To make it truly valuable for users and keep them coming back, you need specific features that deliver insights seamlessly. Here are the essentials:

1. Customizable Dashboards and Reports

Customization is the name of the game. Every app has its own look and feel, and if you’re embedding BI, it better match up. With customizable dashboards, you can tweak colors, layouts, and even the types of visualizations to fit your app’s aesthetic.

This isn’t just about making it pretty; it’s about letting users set up views that actually make sense for their work. A product manager and a marketing director don’t need the same insights, so customizable options let each person tailor reports to their needs, keeping everyone happy and productive.

2. Real-Time Data Updates

Users don’t want stale data from last month or even last week. Real-time data updates are where embedded BI really proves its worth. Imagine an app user watching their sales dashboard tick up with every new deal closed or a customer success team seeing support stats update as tickets get resolved. Real-time data makes insights actionable now, not later, turning your app into an instant resource for decision-making.

3. Row-Level Access Control

When it comes to data, not everyone should see everything.

Developers should look for embedded bi tools with secure server-side tokens (JWT) to ensure each customer can only see their own data. In compliance with SOC 2 & GPDR standards

Example of row-level access control in Holistics.

4. Seamless Integration with Current Systems

Embedded BI needs to slide into your existing app like it was meant to be there all along. The best solutions integrate so well that users barely realize it’s a separate system. It shouldn’t slow down your app, and it should work within your current tech stack. Think about data flow: if users need to export or import data from another source, embedded BI should make this effortless. The goal is to keep users in your app as much as possible without ever needing a detour.

5. APIs and SDKs

Developers want control, and APIs/SDKs are how you get it.

APIs let you tweak and control how data moves and what’s available to users. SDKs, on the other hand, help you add BI components with minimal coding. Together, these features give you a high degree of customization and integration without having to build it all from scratch.

6. White Labeling Capabilities

For many SaaS providers, keeping branding consistent is important. White labeling lets you make the embedded BI tool look and feel as if it were developed in-house. From colors to logos, it matches your brand identity, so users see it as part of the whole experience, not a separate BI module. And for you, this feature means reinforcing your brand with every insight.

Example: White-labeling in Holistics

7. Self-Service Capabilities

The modern user wants to explore data without calling the IT department for help. Self-service BI functionalities let users create their own reports, customize dashboards, and even filter data on the fly.

For developers, this is gold. It means fewer support tickets about creating specific reports or dashboards, letting users explore data on their own. Self-service turns casual users into power users, helping them feel like they’re not just using the app but truly getting value out of it.

8. Interactive Visualizations

Data is infinitely more engaging (and useful) when you can interact with it.

Embedded BI platforms with interactive visualizations let users hover, filter, and even change the visual format on the fly. Interactive charts, maps, and graphs with drill-through and cross-filtering allow users to slice and dice data right within your app, offering a hands-on experience that’s far more engaging than static reports.

9. Data Export and Sharing Options

Data is more valuable when it’s shareable.

Embedded BI should allow users to export their data easily, whether in CSV, Excel, PDF, or other formats. This flexibility means users can share insights with colleagues or clients without hassle. Even better, some embedded BI solutions offer direct sharing capabilities, like email or Slack integrations, so users can share visualizations or dashboards with a single click. For developers, this is a win-win because it keeps data flowing smoothly while meeting users’ needs for collaboration.

10. Data Caching and Pre-Aggregation

When dealing with large datasets, speed becomes a critical factor. Data caching and pre-aggregation allow your embedded BI tool to handle huge data volumes without slowing down performance.

Pre-aggregated data means that commonly used metrics or queries are calculated in advance, speeding up loading times and providing a smoother user experience. Caching further optimizes performance by storing frequently accessed data temporarily, allowing users to access insights in real-time without taxing the system. This feature is essential for SaaS apps expecting high traffic or complex data needs, as it keeps everything fast, responsive, and ready for action.

Of course, not every BI tool has the same caching system. You don't want to work with BI vendors that require data to be loaded into their cache, as this approach often means the tool has to cache more data, making it more expensive to run and cache larger datasets. As a result, data gets refreshed less frequently, making it more likely to get stale. You want to avoid this!

III. 6 Non-negotiable Requirements for Successful Embedded BI

1. Security and Compliance

Data security is top priority, especially when embedding BI in customer-facing applications. Your Embedded BI solution must meet industry-standard security protocols, such as data encryption, secure user authentication, and compliance with regulations like GDPR or CCPA.

For developers, this means ensuring that sensitive data is well-protected, both at rest and in transit. Compliance also helps avoid legal headaches, and it builds trust with users who want assurance that their data is in good hands.

2. Scalability

As your app grows, so do the demands on your embedded BI system. Scalability is about making sure the platform can handle increased data loads, new users, and evolving analytical needs without compromising performance. A scalable Embedded BI solution is designed to adjust to growing user demands, allowing you to add resources, enhance performance, and support larger datasets as you expand. This ensures you won’t need to overhaul the entire system down the line, saving both time and costs in the long run.

3. Performance Optimization

Nobody likes a laggy app, especially when it’s their main tool for decision-making. embedded BI should offer high performance, even under heavy loads or during peak usage times. This means fast query responses, efficient data processing, and quick loading times. Features like data caching, query optimization, and in-memory computing, aggregate awareness can make a world of difference. Performance optimization not only enhances the user experience but also keeps customers engaged, reducing the risk of churn due to slow data access.

4. Cost-Effectiveness

A fancy BI system is great, but if it costs an arm and a leg to maintain, it might not be the best choice. A successful embedded BI solution balances powerful features with affordability, offering pricing structures that work with different budgets. This can mean a range of subscription models, usage-based pricing, or pay-as-you-go options. For developers and product managers, finding a solution that’s cost-effective means you’re not forced to cut back on features just to stay within budget.

4. User-Friendly UI

User experience matters, especially for BI tools that might be used by people without technical expertise. A user-friendly UI makes it easy for customers to explore data, create reports, and gain insights without a steep learning curve. Intuitive navigation, clear icons, and responsive design contribute to a smooth experience. For developers, choosing a BI tool with a well-designed interface saves time on training and support, making it easier for users to get the most out of the embedded analytics.