Machine learning is a term that gets used a lot these days. But there’s a good reason for that. Many forms of technology are being revolutionized because of machine learning. This is certainly the case when it comes to business intelligence technologies.
In fact, 76 percent of executives surveyed by MIT Sloan Management Review said they’re using machine learning to boost sales. This is only possible when machine learning improves the tools available to organizations.
Here are four ways machine learning can make BI better.
1. Far Greater Overall Analytics Capabilities
Machine learning is a powerful technology that allows for far greater analytics capabilities than what has been previously available.
In the past, data scientists and analytics professionals had to spend far more time simply dealing with technology, which limited their ability to do the important work of developing new models and uncovering insights. This has changed, however, thanks to the proliferation of machine learning in business intelligence technologies.
Now, instead of data scientists having to work on BI tools like Dr. Frankenstein, machine learning has led to an era where analytics platforms and data professionals are working in concert. This has clear benefits in allowing data scientists to spend more of their time on higher-level work, as opposed to troubleshooting.
But additionally, machine learning-powered data analytics platforms empower users to achieve far more in drastically less time. This is a clear recipe for success for organizations looking to optimize operations through business intelligence technologies.
2. Spot Anomalies in Data
Humans are great at a lot of things. But there are some areas where they have shortcomings compared to machines. Parsing through large sets of data and being able to analyze it for anomalies is one of them.
However, when deploying machine learning-enabled business intelligence technologies, enterprises can catch anomalies in real time. The benefit to this is pretty clear. When you’re able to identify outlying data points as they occur, you can immediately address the situation, and work to rectify it if necessary.
This is particularly important in today’s world, where so many things are in a constant state of motion. Security breaches, technological malfunction, system failure, and a nearly limitless list of other situations can be solved before causing damage when they’re stopped right away.
It’s also possible for machine learning to help find hidden trends or patterns in sets of data that would never be noticed by humans. This can lead to novel breakthroughs that might otherwise have taken years, or longer, to happen without assistance.
3. Search-Driven Analytics
Machine learning doesn’t just help data scientists and analysts, it can also open up business intelligence technologies to a wider range of people. Undoubtedly, machine learning is playing an important role in the democratization of data. This is where people within an organization without deep data expertise are able to gain insights through user-friendly applications.
Search-driven analytics works much like a search engine for browsing the internet. Users can simply type in queries, and instantly get a result with best-fit visualizations. Without business intelligence technologies leveraging machine learning, search-driven analytics wouldn’t be possible in its current form.
This technology is radically changing how enterprises are able to use their data, as more people can gain insights for more problems in less time.
4. Get a Better Feel for Emerging Trends
Data analytics is all about understanding what has already happened. But what’s the point of that if you’re not going to do anything with that information? This is where machine learning comes into play.
Of course, people can make predictions about what’s going to happen based on data. There are even ways to model likely trends based on statistical probabilities. Machine learning, however, takes things to a whole new level.
This is because machine learning-empowered BI can parse through massive data sets, and not only model potential outcomes, but even give prescriptive recommendations. When seeing into the future becomes as clear as analyzing the past, data analytics is doing an incredible thing.
Machine learning has many applications in modern data analytics. These are just a few of the ways it’s completely changing how enterprises use their data.
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