I was asked to speak recently on a topic that includes two hyped terms: Big data and sustainability. At the risk of igniting an anti-buzzword campaign, I added a third over-used term to that list: analytics. Even though individuals and companies use those three words – big data, sustainability, and
With as much as I travel, I have to confess that I’ve become a bit of a food snob. And for good reason, I might add. Two days in a Chilean hospital will make anyone stick with what they know and trust. After that experience, it was just me and
Principle 4: Completeness – A bank should be able to capture and aggregate all material risk data across the banking group. Data should be available by business line, legal entity, asset type, industry, region and other groupings, as relevant for the risk in question, that permit identifying and reporting risk
What if virtual reality technology allowed you to immerse yourself in big data? That could be your future – and sooner than you think. It happened in August 2013 at the University of Washington: the first direct brain-to-brain communication, with one researcher controlling another researcher’s brain over Skype. Maybe in
In our hyper-connected world, information technology plays a key role in nearly every field and industry. Higher education is no exception, and that’s where EDUCAUSE comes in. This non-profit association works to advance higher education through the use of information technology. One of the primary ways EDUCAUSE achieves its goal
I’ve been to a fair number of SAS User Group International (SUGI) and SAS Global Forum conferences over the years, but I don’t think I’ve been to one as productive, well-organized and fun as this year’s conference in Washington DC. Part of what made the conference very relevant for many
Analytics gives us not just the ability but the imperative to separate our planning activities into two distinct segments – detailed planning that leads to budgets in support of execution, and high-level, analytic-enabled business/scenario planning. My critique of Control Towers in this blog last time led me not only to
Principle 3: Accuracy and Integrity – A bank should be able to generate accurate and reliable risk data to meet normal and stress/crisis reporting accuracy requirements. Data should be aggregated on a largely automated basis so as to minimize the probability of errors. It seems logical that banks would want
Principle 2: Data architecture and IT infrastructure – A bank should design, build and maintain data architecture and IT infrastructure which fully supports its risk data aggregation capabilities and risk reporting practices not only in normal times but also during times of stress or crisis, while still meeting the other
So far in this Ask the Statistician series, we heard statisticians at the Analytics 2013 conference discuss the benefits of statistical analysis, the types of statistical techniques they use to solve their business problems and how they share their statistical results with non-technical audiences that need to use this information. So, the next step
