Data is More Valuable than the Hardware it Runs On

TahomaBlog2

It’s been a while since my last post earlier this year, but we’ve been very busy working on some exciting new technologies that we can finally talk about in public. As many of you know, our original product, the Urika graph analytics appliance (now renamed Urika-GD®), gave us a great opportunity to introduce a unique technology to the enterprise analytics market. Not only did Urika-GD start solving some fairly intractable problems where commodity machines faltered, but it also gave us the opportunity to better understand some of the use cases that were beginning to emerge – how our clients and users actually deployed some of the big data analytic solutions, the workflow from start to finish as well as the other systems that were needed ... [ Read More ]

Oktoberfest: Prost! to Beer and Big Data

Octoberfest_Blog

Bavarian culture has spread its wings and has influenced the world with its beer-drinking tradition. Oktoberfest, a more than 200-year-old celebration that began in Munich, Germany, is still well under way. These days, Oktoberfest is celebrated not only in Bavaria, but also around the globe in places such as London and Dublin and many cities in the United States. As an enthusiast of both beer and data, I find myself thinking about how even beer production and marketing relate to big data. Even in the world of Oktoberfest, there is a massive amount of information to be mined, analyzed and put to use. Questions such as “What types beer are sold the most?” and “Depending on the time, day, place and weather, which areas host the heaviest ... [ Read More ]

Built-in Graph Functions Accelerate Discovery Analytics

We often encounter analytics use cases from customers or prospects where the analyst wants to select a particular facet of the data and deeply analyze it.  For instance, in the healthcare world, data includes patient (including genomic information), procedure, provider, billing and outcome data.  When trying to discover new insights into the data, the analyst often doesn’t know exactly what she’s looking for, so she needs to answer several high-level analytic questions about the data to guide further exploration. (And, of course, today’s data is usually not just big — it’s Big Data, so performance and scalability are important.) Assuming we’ve confirmed that the data is sensible, the high-level analytic questions often include the ... [ Read More ]

I work with superheroes!

mistiblog

The popularity of superheroes is timeless. And no wonder: It’s fun to think about a world populated by heroes with super-human intelligence, the ability to manipulate substances at the molecular level, and supersonic speed. I’ll bet you can guess where I’m going with this. Maybe the summer movie season has put superheroes on my brain, but lately the things that Cray products are doing have reminded me of the superhero feats that excite kids (and grownups – you know who you are). Some of this you’ve read in our blog posts over the last few months. There’s the “Beagle,” a Cray® XE6™ supercomputer at the University of Chicago, which is allowing researchers to test potential new drugs on the entire human genome, rather than only a portion ... [ Read More ]

What Should Your Big Data Strategy Be?

Figure 1. Data driven strategy

In previous articles, I discussed some common big data problems and causes of the problems.  In the final part of this series, we can now get to the icing on the cake – your big data strategy. Read on, my friends. When do you have a big data problem? Since our main interest here is in big data, a fitting question is when do you have a big data problem? The answer is not as straightforward as we’d all like but mostly because we need to have a paradigm shift in terms of how we think about the problem. This HBR article has some really good insight into how data visualization is helping companies understand complex consumer behaviors. The key is to think in aggregates and this is harder than it first appears because finer obvious details ... [ Read More ]