A person using a laptop, presumably using embedded analytics tools

What is embedded analytics?

Embedded analytics refers to functionality that directly embeds customer-facing analytical content from standalone platforms into applications, portals, or websites.

Embedded analytics helps organisations deliver a modern data experience by integrating reports, dashboards, models, data visualisations, and other forms of business intelligence (BI) into one interface. This streamlined view helps you get a clearer picture of your analytics, form deeper insights, and make faster, more data-driven decisions.

How to use embedded analytics tools

Now you know how to define embedded analytics. But what is embedded analytics used for? How does it work and what can you do with it?

In today's digital landscape, many companies aspire towards a data-driven culture where users may easily access the information they need. However, the challenges of integrating, managing, analysing, securing, and sharing data prevent them from doing so at the scale they need. That’s where embedded analytics comes in.

Organisations and independent software vendors (ISVs), or software developers, rely on embedded analytics solutions and software to bring new context, efficiency, and value to their existing data. Corporations use embedded analytics to consolidate their data sources and BI tools so that data can be easily read, analysed, and secured from within a single familiar interface. Software companies use embedded reporting tools to introduce reports and visuals into the apps they build, saving time and resources.

Embedded analytics examples

Embedded analytics also benefits the end user by providing them with the ability to conduct many forms of self-service BI within a single app, all without having to toggle between systems. As a result of this more intuitive workflow, it’s now more convenient than ever to analyse, share, and gain deeper insights from your most up-to-date data. Here’s what you can do with embedded analytics to:

  • Generate and embed dynamic and intelligent reports featuring visually striking charts and graphs.
  • Create and integrate custom dashboards, reports, visuals, and data models based on your most up-to-date performance metrics.
  • Connect, extract, and consolidate data from multiple sources into one single source of truth.
  • Customise the look and feel of data presentation within your own branded, white-label user interface.
  • Conduct benchmarking tests against historical industry data.
  • Enable self-service or ad-hoc BI analysis for any user.
  • Enable secure and reliable access to mobile reporting.
  • Protect sensitive data by monitoring user access and meeting compliance standards.

Benefits of embedded analytics

With proper access to data comes smarter decisions, greater efficiencies, and a plethora of other advantages. Here are some reasons why you should consider embedding your analytics and BI:

  • Save on development time and resources By embedding analytics rather than building the content out themselves, product teams can focus more on building out core features, allowing them to get to market faster. Automated monitoring and deployment tools may also help reduce cost and resource usage.
  • Provide users with easier access to data Many embedded BI platforms offer in-app, self-service analysis and AI features so that you can get what they need without having to put in an analyst request. This results in greater familiarity with the data, deeper insights, and the fostering of a data-driven culture.
  • Upgrade to a more modern data experience Feature-rich reports and dashboards give you the ability to interact with your data in a more immersive way. This leads to more meaningful insights, greater user satisfaction, and an in-app experience that stands out from the rest.
  • Boost productivity With all your analytics available in one interface, you’ll no longer need to toggle between different platforms to find what you need. This results in increased productivity, more value, and a greater return on investment.

What’s the difference between embedded BI vs. traditional BI?

Traditional BI refers to a suite of tools or processes that collect, transform, mine, visualise, model, and secure data from one or multiple sources. Historically, these tools and processes have been primarily used by data analysts to programmatically uncover trends from large datasets, though today’s more modern platforms offer greater self-service options for business users as well. The derived insights can then be shared across the organisation in the form of reports, dashboards, charts, and graphs.

Embedded BI not only offers the full benefits of traditional BI, but it also expands access to content by placing it inside the apps that people already rely on. A sales team, for instance, might want to embed a streaming feed into a CRM system, messaging app, or internal tool so that all their newest metrics can be found in one place. This also opens the data up to a suite of connected, in-app integrations, allowing your team to collaborate more efficiently using powerful new tools.

Embedded analytics and API management

Embedded analytics would not be possible without the support of application programming interfaces, or APIs. APIs enable apps to communicate with each other through a variety of protocol requests. This gives you the ability to plug third-party components into your system without having to build these tools yourself. It also ensures that the two systems remain connected so that changes to the code on one end are securely and reliably transmitted to the other.

Today’s most innovative organisations are adopting an API-centred architecture to streamline workflows, spur growth, and innovate faster. That’s because APIs provide added value, flexibility, and security by introducing new functionality to apps in the form of integrations. Integrations determine how BI content—data sources, dashboards, reports, and other add-ons—gets embedded, managed, automated, and customised according to the look and feel of the interface. They also determine how that content interacts with each other. This is typically accomplished by generating a token, which gives the app permission to access information on the server side. Once access has been given, the information then gets copied over to the client side.

Large organisations use hundreds, if not thousands, of internal and external APIs in their day-to-day operations. Effective API management is crucial for optimising traffic, authenticating users through features like single sign-on (SSO), meeting security and compliance requirements, and quickly deploying new APIs—all essential aspects you should consider when building an embedded experience.

How to implement embedded analytics

When designing and implementing an embedded analytics solution, start by defining the high-level business goals of your organisation, as well as the nature and size of your organisation. Are you looking to streamline operational processes for your organisation, or are you looking to get your app to market faster? Are you looking to unify all your data sources and tools into a CRM, or are you providing out-of-the-box analytics features to your customers?

You’ll also want to consider your end users. Who are they? How might they interact with the data they encounter? Which features might bring them the most value? This will help you deliver user experiences that are tailored to your customers’ needs.

Next, assess your current infrastructure to see what’s working, what could be improved upon, and whether to build these features out internally or to buy an out-of-the-box solution. The build vs. buy decision is dependant on a variety of factors including desired product functionality, timing, budget, availability of resources, and the overall return on investment. Every organisation’s needs are different, but if you do decide to buy, you’ll want to review BI solutions that offer API integrations for easy embedding.

Finally, you’ll need to plan for security, authentication, and data protection. Consider how access to data will be managed among internal users and external users, as well as the method of authentication. Determine how you will secure API connections, manage traffic flow, and enable encryption if needed. You’ll also want to make sure your BI content meets regulatory data residency and compliance requirements throughout your regions of choice.

Embedded analytics solutions and software

Now that you know how to get started, let’s dive into recommendations for embedded analytics solutions and software. The nature and complexity of your needs will help determine which tools and technologies to invest in, so you’ll want to do your research.

First, you’ll need a standalone BI solution to start with. This solution should have the ability to bring together third-party data sources, and to keep that data protected through security tools. Most importantly, it should give your users access to the data, tools, and insights they need. A desktop solution like Power BI combines an intuitive interface with powerful analytics, allowing you to create, analyse, and share interactive reports, data visualisations, and models. It can also scale up and down depending on your organisation’s infrastructural needs.

After evaluating your BI solution, the next step is to establish your use case for embedding. If you’re looking to embed for your organisation, then you’ll want to look at cloud solutions geared primarily towards internal users. In this scenario, each user must have a licence in order to gain access to embedded content. When they log onto the internal app or tool, it will ask them for login credentials. Large organisations should consider an enterprise-grade cloud solution with embedding capabilities, like Power BI Premium, to ensure that their needs are being met at scale.

If you’re looking to embed for your customers, then you’ll want to look at solutions that allow external users to access embedded content without a licence or login credentials. In this scenario, the BI solution is white labelled as a built-in feature of the app. Software companies should look into cloud-based embedded analytics solutions developed specifically for white labelling, such as Power BI Embedded, so that they may provide their users with value while saving on development time, cost, and resources.

Embed for your org

  • Target audience Corporations, large organisations, large ISVs
  • Data ownership User owns data
  • User type Internal
  • Licensing Each user needs a licence
  • Authentication Authenticate against bundled cloud identity service; interactive
  • Recommendation Power BI Premium

Embed for your customers

  • Target audience ISVs, software developers
  • Data ownership App owns data
  • User type External
  • Licensing Each user doesn’t need a licence
  • Authentication Use own authentication method; non-interactive
  • Recommendation Power BI Embedded

Start embedding with Power BI

Provide a modern data experience to users in your own app with the scalable platform for self-service and enterprise BI. Learn about features, browse customer stories, and try it for yourself using the embedded analytics playground.

Frequently asked questions

What is embedded analytics?

Embedded analytics refers to functionality that directly embeds analytics from a standalone platform into a single software or business app, website, or portal.

Why is embedded analytics important?

Organisations and independent software vendors (ISVs) across a variety of industries use embedded analytics to get to market faster, improve user experience, and increase productivity.

What are embedded analytics tools?

Embedded analytics tools allow you to create and share reports, graphs, and visualisations from directly within an app. They also enable benchmarking, self-service querying, and other forms of BI.

What is embedded analytics software?

Embedded analytics software gives you the ability to embed reports, dashboards, and other analytical content through a variety of APIs. You’ll typically need to purchase a licence in order to use these integrations.