A few week’s back I wrote about the data translator – a role on the data science team that bridges the gap between the data scientist and the business. That got me thinking – what are the characteristics (that may be less obvious) that make for a good data analyst? 1. Intellectual curiosity and focus…
Poor data quality is the single biggest contributor to the poor performance of customer risk-rating models. Incorrect know-your-customer (KYC) information, missing information on company suppliers, and erroneous business descriptions impair the effectiveness of screening tools and needlessly raise the workload of investigation teams. In many institutions, over half the cases reviewed have been labeled high risk simply due to poor data quality – McKinsey
Big Data has become a buzzword in recent years as businesses have discovered new ways to collect valuable information about their customers and processes. The advent of mobile tech coupled with the Internet of Things (IoT) has given companies new ways to collect data, while machine learning has given analysts the tools needed to discern…
The data translator bridges the gap between the data scientist and the business
We all know the three V’s of big data – volume, variety and velocity (it’s big, it’s complex and it changes rapidly). Recent events got me thinking about the three E’s… Explosiveness We have been hearing for years of the massive volumes of data being generated every second, yet, for most businesses the examples used…
Artificial intelligence and machine learning are the new “big data’ – the hottest topic in analytics and decision making. The premise – that computers that can think and learn, like humans, can replace humans for many tasks.. Projects like driverless cars; the Internet of Things (IoT) – where machines and devices contaminate amongst each other…
It’s certainly not a new refrain, but in recent years IT managers are increasingly being told to do more with less – even as the number of new projects and requirements increase. Data is the fuel that powers most new business initiatives, but each project needs a slightly different blend of data sources and data…
