Predictive analytics has come a long way and, in an era defined by the ever-increasing influx of data and heightened customer demands, businesses no longer can deny its strategic importance. Industries such as insurance, financial services, and retail have used predictive analytics for decades, while others are just getting started. So what’s new? Predictive analytics
We explore the ins-and-outs of the algorithmic economy It’s no good just having data – it’s what you do with it that counts. In five years, one million new devices will come online every hour, creating billions...
2015 was a tumultuous year for Big Data, with highs continuing to dazzle us with the potential world-changing power of data and analytics. At the same time there were plenty of lows serving as ongoing warnings that...
The use of wireless technology for asset tracking has taken off over the last decade. Consumer retail was the first industry to adopt this technology for location services by tagging product pallets with radio frequency ID (RFID) tags....
The reason for Hadoop’s success in the banking and finance domain is its ability to address various issues faced by the financial industry at minimal cost and time. Despite the various benefits of Hadoop, to apply it...
More organizations than ever before are putting the right data on the right platform for the right reason. This new level of data efficiency greatly reduces – and, in the long run, may ultimately eliminate – the...
When you hear the term “data scientist,” you probably think of finance or meteorology or maybe a sports-managing savant like Jonah Hill in Moneyball. But that’s all about to change. It’s no longer just baseball recruiting or...
Gaffer a graph database “optimized for retrieving data on nodes of interest” developed by the notorious UK spy agency GCHQ is available for download. You can now run and improve it because they’ve posted it to Github...
Big Data analytics is now being applied at every stage of the retail process – working out what the popular products will be by predicting trends, forecasting where the demand will be for those products, optimizing pricing...
We’ve organized data science blogs across eight different categories: Machine learning, Hadoop, R, Python, business intelligence, data visualization, statistics, and a general data science bucket. Data about their reader count comes from Feedly. This is a work...
