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

Citigroup and AIG talk big data

Jill Dyché, internationally recognized speaker, author and business consultant, spends her days talking to businesses about big data – how they’re using it, challenges, successes, strategies, plans and more. What she’s hearing again and again from IT leaders is that they have to innovate with big data, move quickly and

Alison Bolen 0
Big data lessons from Google Flu Trends

The Google Flu Trends application has received negative press since 2013 over its inability to accurately detect flu outbreaks. The latest critique, “The Parable of Google Flu: Traps in Big Data Analysis,” from Science magazine compares Google Flu Trends data to CDC data and dissects where the Google analysis went

Tom Morse 0
Big Data… What it means to you

From time-to-time marketers, journalist, and thought leaders find ways to describe things in a new way.  It’s a time-honored tradition guaranteed to attract eyeballs and sell books.  Lately there has been a lot of buzz about the Internet of X, a way of describing a uniquely identifiable collection of objects

David Pope 0
Twas the night before big data

Twas the night before "big data," when all through the data center Not an IT supervisor was stirring, not even the help desk on-call. The servers where all humming along nicely in hopes Big data would soon be there.   The business users were nestled all snug in their offices

Analytics
Alison Bolen 0
Big data and Hadoop at Lenovo

For Lenovo, the No. 1 goal in terms of analyzing big data is to "better understand our consumer and hear their voice," says Anthony Volpe, Chief Corporate Analytics Officer at Lenovo. Big data sources for the personal technology company include social conversation data, consumer device usage data, survey data and

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