Embedded Analytics Defined

Embedded Analytics Defined

Embedded analytics is a fairly new concept to the world of business intelligence tools. Despite this, it’s quickly becoming one of the most essential and functional capabilities you should look for when thinking about adopting new platforms.

But what is embedded analytics, exactly? When looking for a definition of embedded analytics, research firm Gartner provides a great explanation: “Embedded analytics is a digital workplace capability where data analysis occurs within a user’s natural workflow, without the need to toggle to another application.”

Boom. That’s about as concise of a definition of embedded analytics as you’re going to find anywhere. The important thing to note here is the aspect of having analysis deployed in the way that’s most convenient to a user’s workflow. Instead of having to switch between a handful of different BI tools in order to do one’s job, embedded analytics allows for all the important elements of these disparate tools to be combined in one place—making for a highly effective, personalized experience.

Now that you understand the fundamentals of what embedded analytics is, it’s time to dig into some of the specific capabilities of this technology.

What Are the Benefits of Embedded Analytics?

There are many reasons enterprises might be motivated to adopt embedded analytics into their business intelligence. Here are some of the most prevalent benefits of embedded analytics for organizations:

  • More efficient than traditional BI – No matter how you cut it, older BI tools have back-and-forth built into the design. If you’re able to run your own analysis, or have a dashboard in multiple tools, it’s a pain to have to be constantly switching between these. If you’re not a data expert, it’s frustrating to have to send endless queries off to an analyst, who probably has more pressing projects that require their knowledge. Embedded analytics solves all these problems by making it possible to bring insights directly to user workflows.
  • Reduce compliance risks – Having your BI tools perform like a frenzied symphony of semi-independent processes is a recipe for trouble. Not only does this hamper the effectiveness of employees, it can create very real compliance risks if data is being used in roundabout ways, as it creates more surfaces for things to go wrong. analytics solves this by eliminating much of the redundances that would otherwise be problematic.
  • Wider availability of data – Whether you’re working to foster a data culture within your organization, or simply want to open analytics processes to more people, embedded analytics can help facilitate these goals. The ability to place things exactly where they make most sense makes it so more people than ever can benefit from having their hands on data, without creating risks of breaches.
  • Build stickier tools – analytics can be an essential piece of building an analytics tool that’s truly sticky for users—whether internal teams or external clients. The ability to make customizable experiences for users through analytics will keep them coming back over and over again.
  • Automate certain processes – When you utilize analytics, you can also automate many processes that can otherwise be a chore. For instance, you can automate elements of interaction between external apps, which leads to a more fluid and less cumbersome experience for users.

When looking at all these benefits together, it seems pretty clear that analytics is a powerful tool for revitalizing business intelligence with an organization. Should your enterprise consider adopting platforms outfitted with analytics capabilities? While no two places are exactly alike, that in itself is a sort of argument for the utility . Businesses that want to take their data usage to new highs should consider how analytics can help them achieve more.

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