Embedded Analytics and AI

Good piece, below the intro.   Embedded yes, but the best way how? 

Embedded Future of Analytics and AI

Alex Woodie

Data makes the world go round; you won’t get much argument from us on that. But if there’s one thing better than having the right piece of information, it’s having it at the right time. And that, in a nutshell, is why embedded analytics and AI will be so critical to big data’s future.

Despite the progress we’ve made since the big data revolution began, access to data and data tools is still largely restricted to a select few. In many companies, it’s the BI dashboard-wielding business analysts who ask tough questions and the data scientists who really dig in to spot patterns and anomalies that can be monetized, often through machine learning and AI-powered automation.

But that leaves the bulk of the regular works out of the data loop. While the customer service representatives, bus drivers, and teachers may not have the SQL skills of a Tableau or PowerBI power user, they do have ample opportunities to impact the business through data. But currently they’re not given the opportunity because they don’t have the right tools.

One of the folks who is dedicated to closing this information access gap is Amir Orad, the CEO of Sisense, which is one of the top five providers of embedded analytics solutions, according to Nucleus Research.

“Gartner shows 80% of all employees don’t leverage BI or insights because it takes skills and learning. You have to go to another system and log in. It’s too much,” Orad tells Datanami. “I’m a big believer that insight will be embedded in everyday tools people use, and stop being as much as possible a side tool to come to and ask ridiculous questions, and that will truly open the other 80%.”

Nucleus Research Senior Analyst Alexander Wurm, author of the recently released Embedded Analytics Technology Value Matrix 2022 report, would likely agree with Orad’s assessment.

“The embedded analytics market has taken off in parallel as organizations look to empower internal departments with analytics embedded in the applications they already use, and many consumer-facing businesses are embedding analytic capabilities to differentiate their products and elevate their customer experience,” Wurm writes in the report, which you can access here.

(Source: Nucleus Research)

“To support this broadening adoption, embedded analytics providers are investing in complete cloud services to enable data discovery, modeling, reporting, and visualization creation within external applications and compete to deliver highly usable services to empower analysts, creators, and end-consumers,” he continues.

Several different types of companies are turning to embedded analytics. Tech firms and ISVs are looking to embedded analytics to “elevate end-user experience and unlock additional revenue,” Wurm writes, while less technical teams have also embraced embedded analytics as a way to enable data democratization.

“This is crucial for business-level users who may not be familiar with statistical methods but can be taught to turn data into relevant insights with the correct tools,” he writes.

The broader BI and visualization tool market is turning to machine learning and AI, which is a trend that IT analyst groups like Gartner have been documenting for years. Nucleus says the embedded analytics market is also adopting ML and AI, as well as natural language query (NLQ) and natural language generation (NLG) tools. Industry leaders like Sisense, Domo, Tableau, Oracle, and Infor Birst are leading the way with NLG and NLQ capabilites, and the rest of the market is about 18 months behind, Wurm writes.  ... '