Urika-GX: A Game Changer for Big Data Analytics

There’s a lot of hype around big data in healthcare and the life sciences. But big data is here to stay. Information is what drives the entire industry. When I worked in big pharma, I learned that the product of a pharmaceutical company is not a pill, it's a label. And a label is just a specific assemblage of information, carefully distilled from terabytes of information collected and analyzed over the course of many years by many intelligent people. To compete, companies have to be very good at turning data into information, and information into knowledge. The stakes couldn't be higher, because every day millions of patients rely on the quality of this data and the strength of the analyses done by researchers. Analyzing big data is ... [ Read More ]

Graph Databases: Key Thoughts from Online Chat

It’s pretty interesting to see graph analytics gain traction in the work of big data. We’ve been focusing on graph databases to round out Hadoop® and Spark™ ecosystems and allow for more advanced analytics — and enable people to uncover never-before-seen patterns. (Tell me that’s not cool!) From solving real-world problems such as detecting cyberattacks and creating value from IoT sensor data to precisely identifying drug interactions faster than ever before, graph has become a powerhouse in looking at complex, irregular and very large datasets to identify patterns in near real-time. On March 16, we hosted an online chat titled “Graph: The Missing Link in Big Data Analytics” with industry experts from Deloitte and Mphasis. Sixty-one ... [ Read More ]

Graph: The Missing Link in Big Data Analytics

Graph analytics is gaining traction in the world of big data and IoT. From solving real-world problems such as detecting cyberattacks and creating value from IoT sensor data to precisely identifying drug interactions faster than ever before, graph has become a powerhouse in detecting never-before-seen connections and emergent patterns. It’s critical to understand how graph can be added to traditional Hadoop® and Spark™ workflows for successful results. Join us Wednesday, March 16, for a live online chat, “Graph: The Missing Link in Big Data Analytics,” to learn and discuss all things graph analytics. You can easily participate using a Twitter, LinkedIn or Facebook account. Hear from industry experts from Deloitte, Mphasis and Cray who ... [ Read More ]

Top 5 Blog Posts From 2015

Happy New Year! Check out some of the top blog posts from 2015: Why Do Better Forecasts Matter? Meteorologists have been striving to increase the accuracy of their work since the first weather forecasts were issued in the mid-19th century by pioneers such as Robert FitzRoy. In the 1950s and 1960s, the development of computers and observational technologies enabled forecast generation using the numerical weather prediction theories of Vilhelm Bjerknes and Lewis Fry Richardson. Today the numerical models that support our weather and climate forecasts are true “grand challenge” problems, requiring on the order of 10,000 billion (1016) mathematical operations and the exchange of 150 billion (1.5 x 1014) bytes of information to generate a ... [ Read More ]

The Best Practices are No Longer the “Best” Practices – Part II

Earlier this week, I shared my views about best practices and cybersecurity. Now I want to move beyond best practices as your sole defense. The traditional cybersecurity mindset is one of prevention, believing threats cannot penetrate — and this is why security plans fail. It’s easy to assume defenses are successful against an insidious threat. Metrics will show an effective compliance program, intrusion detection and access denial. Yet to take for granted that the threat is gone, rather than having simply moved to another path within your network, is foolhardy. Assuming there are numerous threats to your security measures that are coming in a dynamic and continuous fashion may seem paranoid, but just because you’re paranoid doesn’t mean ... [ Read More ]