A few years ago, I combined my day job as a data engineer, helping customers engineer data analytics, with my love for  football and set out to beat the bookies. It’s an exciting game to play, and I have learned a lot about the merits of different predictive models that

Simply put, non-subscription churn happens when users or customers, who can end their relationship with your business at any time, leave your website or sales funnel. These types of customers may gradually reduce their purchase frequency over time, or they may all of a sudden never buy again. Companies in nearly

The creation and consumption of data continues to rapidly grow around the globe with large investment in big data analytics hardware, software, and services. The availability of large data sets is one of the core reasons that Deep Learning, a sub-set of artificial intelligence (AI), has recently emerged as the hottest

Researchers have estimated that 25 years ago, around 100GB of data was generated every day. By 1997, we were generating 100GB every hour and by 2002 the same amount of data was generated in a second. We’re on trajectory – by 2018 – to generate 50TB of data every single

Social networks, in one form or another, have existed since people first began to interact. Indeed, put two or more people together and you have the foundation of a social network. It is therefore no surprise that, in today’s Internet-everywhere world, online social networks have become entirely ubiquitous. Within this

Emerging technological breakthroughs enter our consciousness promising a bright future, but more often than not they follow Gartner’s well plotted hype cycle – from the peak of inflated expectation through the trough of disillusionment, before mainstream adoption materialises. Some technologies, however, take on a new meaning after a prolonged maturity

The travel industry is no stranger to Data Science disruption – especially air travel. Online flight finders have been snapping up data scientists from other industries in order to make better use of the available data, and airlines have been building and opening APIs. Many services are using this opportunity

Big data is a big deal. Unfortunately, due to the sheer volume and velocity at which its created, many organizations still struggle to make sense of their data. Furthermore, because data is dispersed across so many disparate platforms (e.g. marketing automation, CRMs, Google Analytics, etc.), it’s become increasingly difficult to

With passengers once again left frustrated by rail delays and disturbance over the Easter period, UK rail operators will no doubt face further scrutiny over the quality of service they are providing commuters. With services frequently disrupted by signalling problems, broken-down trains and congestion, the industry, the Government and, of

Through my work with customers and data scientists building predictive applications based on the Blue Yonder Platform and integrating our standard products, such as Forward Demand, into customer workflows, I’ve encountered a few common prediction pitfalls. While these might not ruin the scientific validity of the model, they may affect