We all know how important data is for organizations. Now, how can we practically perform data analysis and gain insights that can bring a competitive edge to the company? To achieve this goal, we need to combine knowledge and technology.
In the field of technology, we have machine learning, which is the ability of machines to learn and improve from data without being explicitly programmed for it. Instead of following a fixed set of rules, machine learning algorithms can identify complex patterns in the data and make predictions or decisions based on these patterns.
But don’t be scared if this is your first time encountering this topic. There are indeed companies that invest heavily in this area, but even if your company is small or medium-sized, it can still benefit. At the end of this post, I’ll give an example of how we can apply machine learning in Excel to make predictions, for example, about whether someone is likely to be a good or bad payer based on their characteristics.
“Credit scoring” (credit risk modeling) involves applying statistical techniques and machine learning to predict the probability of an individual being a good or bad payer based on their financial, behavioral, and historical characteristics.
And, of course, we can apply machine learning to many other situations: automating processes, detecting fraud, recommending products and services, and much more.
Remember when I mentioned that we need to combine knowledge and technology? Well, technology plays an important role, but it’s necessary to develop processes that ensure its proper application. In this regard, seek out qualified professionals with experience to assist you.
Do you have any questions or would like to learn more? Get in touch.
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