Real Life Applications of Advanced Analytics

Hearing the term “advanced analytics” sounds a little bit like something that would come out of the mouth of Napoleon Dynamite. But the truth is advanced analytics are seriously powerful, and are reshaping how enterprises use data. Research firm Gartner defines advanced analytics as “the autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations.”


In essence, advanced analytics harness the power of cutting-edge tech, such as artificial intelligence, machine learning, and neural networks, to massively increase the potential output of business intelligence tools. While this might not make total sense yet, there are some compelling real-life applications of advanced analytics. Understanding how these tools can be used by your organization can take operations to totally new highs.


What Are Some Practical Applications of Advanced Analytics?

Now that you have a basic grasp of what advanced analytics is all about, it’s time to look at some more specific uses. Here are a few real-life ways enterprises can benefit from adopting advanced analytics tools:


  • Easily identify hidden patterns – With more traditional business intelligence, finding hidden patterns is no different than looking for a needle in a haystack. On the other hand, advanced analytics has the power to quickly identify trends that would be completely invisible to the naked eye. Through AI-driven analytics tools, organizations can find insights that otherwise might never have been uncovered.
  • Find signal through the noise – Many enterprises have an obscene amount of data—much of it totally unused. In the past, all this information was just taking up space, as no one was really doing anything with it. Now, however, advanced analytics can help cut through the slog of endless data to find what really matters. Due to this, even organizations with an overwhelming amount of data can easily get right to the meat of it.
  • Dig deeper into the data – People who have spent time working with more traditional BI tools—or even just sending off requests to the analytics team—know the feeling of wanting answers, but not quite being able to have them. Advanced analytics has the power to shed light on things that previously had to be left unknown. Through the power of AI and machine learning, it’s possible to analyze more variables than ever in just a fraction of the time. Furthermore, certain advanced analytics platforms can actually help guide the insight process. AI-powered tools can give recommended follow-up queries based on previous requests. This can take you to solutions that otherwise might have never occurred to you without the aid of advanced analytics.
  • Find the real sources of friction – Oftentimes, data analysis with the old kind of BI can lead to you finding something that seems like a revelation, but is actually just another dead end. This isn’t just a waste of time, it can lead to enterprises making poor decisions based on incomplete truths. Advanced analytics can take you to the real roots of issues, which can help rectify inefficiencies the first time, without having to run in circles.
  • Eye up the competition – In some industries, running your own business is only half the battle. When you’re up against highly innovative, fast-moving organizations, you need to have the foresight and agility to stay ahead of their moves. Advanced analytics can help with things like market and customer evaluations, so you can better understand what potential clients and products are worth pursuing, and what just isn’t going to work.


Clearly, there are some really strong reasons for bringing advanced analytics into your enterprise’s BI arsenal. There’s no shortage of real-life applications for advanced analytics—and this list will only continue to grow.