Embedded Analytics

Embedding from Light to Deep and Beyond

Embedding Analytics from Light to Deep and Beyond

Watch this video to learn how embedding analytics can be simple or complex depending on the use case.

Simple white labeling is really just rebranding one company’s product to make it appear as its own. White labeling traces its roots all the way back to promotional practices used by record companies -- vinyl records.

But embedding can also encompass deep integrations that include customized visualizations and connectors to customer-specific, proprietary data sources. In between those two extremes are other options, including lightweight integration with iFrames and API-based embedding that requires use of an SDK.

Transcript

There are a range of styles of embedding from white labeling through to lightweight integrated to API embedding through to extended.  I'm gonna talk now about each one of those.

White Labeling

So, with white labeling, this is all about rebranding the application to make it look and feel like your application.  So, this could be changing colors, changing fonts, adding your company logo, whatever it takes to make the analytics you're embedding look and feel like your application.

Lightweight

The second option is lightweight integrated.  This is typically using iFrames, so within the web application embedded iFrames containing the visualizations and the dashboards that you want to embed and with parameter passing from the parent application.  So, interacting with the parent application and those visualizations and those dashboards are being updated appropriately.

API Embedding

The third option is kind of going deeper.  This is API embedding.  This is using the software development kit or SDK for a very deep, seamless integration where literally the two applications become blended into one and you really can't tell the boundaries between one or the other.

Meeting Custom Integration Requirements

And then, finally, you have extended, and this is for meeting custom requirements where, in particular industries, maybe there's certain visualization styles and types, and you need to add those visualizations to the analytic package.  And the other part of that is data sources.  All the time, we see more and more emerging modern data sources or maybe homegrown data sources.  So, this is the ability to extend the underlying analytics application to take to encompass those unique data sources.

Embedding from Light to Deep and Beyond

Watch this video to learn how embedding analytics can be simple or complex depending on the use case.

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