Professional sports lend themselves really well to economic calculations – players, coaches, and agents act similarly to the hypothetical, rational decision-makers in economic models. While this data may seem complex or hard to obtain, it’s actually all readily available online – you just need to know where to look, how

BI can help you start making sense of your data, but it still expects you to do the heavy lifting when it comes to finding insights. Building predictive models that can cut down your decision time and offer better insights is a must, but achieving them sounds impossible.  So, why

To guide your company towards success, leaders need a clear idea of what’s around the corner. It’s not enough to analyze what happened in the past. You need to know what the future holds. And that means data science-backed predictive models.  More data science doesn’t always mean more data scientists, though.

The number of people searching for nearby jobs has skyrocketed in the last three months due to various factors like the current coronavirus pandemic. Data acquired by Finbold indicates that based on queries logged on the search engine Google, the global interest in the phrase ‘job hiring near me’ grew

Fraud is at a record high – nearly half of all businesses had experienced fraud in the past two years. This excerpt of the Explorium’s guide on enhancing risk models explains how to build them better in three steps. Every few years, whether global, local, or industry-specific, a major event

Being a data scientist is hard. In addition to the combination of advanced mathematics and coding skills required to do the job, it’s a newer role for many organizations, so data scientists are called upon to navigate corporate landscapes, source the right IT resources, and establish new workflows across departments