Tag: high-performance analytics

Internet of Things
Natalie Mendes 0
The analytics of things ... and sports

Who cares about sports and data? Not just athletes, coaches and fans. It turns out that many companies outside of sporting organisations are also associated with the sports industry.  For example, financial services organisations are actively involved in sports sponsorships. Retailers sell fan merchandise. Telcos build social engagement strategies around

Tom Stock 0
Decisions first!

I moved to Australia from Belgium two months ago for a short-term assignment. I am very concerned by the exchange rate. My dollars have lost over 15% of their value in euros and I share my frustration around me. People tell me, "Just wait, it cannot stay so low, the

Stuart Rose 0
Putting predictive analytics to work.

Insurance relies on the ability to predict future claims or loss exposure based on historical information and experience. However, insurers face an uncertain future due to spiraling operational costs, escalating regulatory pressures, increasing competition and greater customer expectations. More than ever, insurance companies need to optimize their business processes. But

Craig Rubendall 0
Big data meets open standards

Imagine choosing one application for Linux that worked on the version you currently use. You choose another program but find that it doesn’t work on that version of Linux. A third application? It works with another version of Linux. Luckily, that rarely happens. In 2001, the Linux Foundation established Linux Standard

Felix Liao 0
Three Things You Should Know About SAS and Hadoop

I have been on a whirlwind tour locally here in Australia visiting existing SAS customers where the focus of discussions have centered around SAS and Hadoop. I am happy to report that during these discussions, customers have been consistently surprised and excited about what we are doing around SAS on

Data Management
Anne Belder 0
Hadoop: the game-changer in banking

At most banks, data is stored in separate databases and data warehouses. Customer data is stored in marketing databases, fraud analyses are done on transactional data, and risk data is stored in risk data warehouses. Oftentimes even liquidity, credit, market, and operational risk data is stored separately as well. Bringing

Mark Torr 0
How Hadoop emerged and why it gained mainstream traction

In the world of IT, very few new technologies emerge that are not built on what came before, combined with a new, emerging need or idea. The history of Hadoop is no exception. To understand how Hadoop came to be, we therefore need to understand what went before Hadoop that led to its creation. To understand

Analytics
Carl Farrell 0
Energized about energy

I’ve been told I have rocks for brains before, but right now I have rocks on the brain – the kind that are millions of years old and contain precious stores of oil and gas. One reason I have petroleum on my mind is that I’ve just returned from Brazil, where

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