Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.
The value and benefits of becoming a data scientist or picking up basic data science skills, cannot be overstated in today’s world. Businesses across all industries are starting to embrace data analytics and those who aren’t will soon feel the advantage gained by their competitors who are.
Learning rarely stops after your formal education ends, whether you’re pursuing further learning out of personal interest, career-aspiration or it’s mandated by your company. Most companies offer funding and support for their employees to go on courses to keep their skills up to date or learn new skills. Companies spend millions every year on enabling employees to participate in physical, often off-site training, and the costs can cover training fees, training material, travel and accommodation.
The Simpson's Paradox is a phenomenon in statistics illustrating how easy it is to misinterpret data. (Click to Tweet!) It occurs mainly in descriptive and diagnostic analytics (see our blog on the different types of analytics) where an analyst may jump to a conclusion driven by motivated reasoning and not by objectively assessing the evidence.
As part of our blog series on cognitive biases and logical fallacies that data scientists should avoid, today we address a prevalent logical fallacy: the "correlation proves causation" fallacy. Correlation due to causation is just one of the five main categories of causation, and this blog will look into each of the five.
During the last year, we’ve experienced the escalation of social issues around artificial intelligence (AI), with Elon Musk leading the charge. Musk continues to advocate the idea that humanity is getting closer to a Skynet-like future – to many people’s concern. One of the very real and valid concerns is the idea that many existing jobs will be automated, thanks to AI.