In our last blog we explored the potential impact of missingness in data in terms of its impact on models which require complete case analysis. We took a simple view that data was missing with an equal, independent, probability for any given model input. This week we explore cases where
During the pandemic, millions of people have made the leap to digital banking. Identity analytics can help banks provide a delightful customer experience while keeping fraudsters out in the cold. Fraud is often seen as a cost centre for banks, but there’s an opportunity for fraud teams to become a
As a huge road cycling fan, one of my favorite Olympic events is track cycling. With its speed and intensity, it is such a captivating set of events. While some events are sprint-focused and others are more endurance-focused, they all require powerful physical abilities, great bike-handling skills, cunning tactical expertise
In the previous section of this series we discussed ways of assessing the relationship between variables. This week we change the focus to the shape and sparsity of our dataset. One area of Explanatory Data Analysis which we’ve missed so far is the impact of missingness in data. Having missing
In the previous section of this series we looked at basic summary statistics. In this article we start to consider the relationships between variables in our dataset. As part of your Explanatory Data Analysis it is worth looking for correlation between variables. Generally, when referring to correlation we mean the
Within both the business world and our personal lives, data is becoming increasingly intrinsic to everything we do. Whether it’s picking which restaurant to order from, a tailored advert or figuring out the quickest route home, data is a part of our everyday decision making. For businesses, the value of
Economists and forecasters have painted a gloomy picture of the impact of the COVID-19 pandemic on UK society. The impact of lockdowns and travel restrictions on many sectors of the economy was expected to put businesses at risk and pull millions of families into financial hardship. In the energy and
Beloved Dummies: Let’s demystify another #AI-hype today: predictive maintenance. Yet another one of these buzzwords that require batteries of #DataScientists and truckloads of programmers. Let me show you how Dummies like you and me can address this. What is predictive maintenance? So we’re talking maintenance of machinery. Sure, you can
If the big banks won’t help when times are tough, customers will turn to smaller, simpler providers. And once they’ve switched, banks will struggle to win them back. I’ve written before about how banks are an essential part of the UK’s social fabric. Our economy depends on the availability of
Following on from my last blog introducing the series, in this section, we’ll take a first look at Explanatory Data Analysis with basic summary statistics. Getting started with a new dataset in analytics can be daunting. It can help when first looking at a dataset to start with basic summary
