Ariella Brown, Technology Blogger, 5/22/2013 Comment now
Have you ever asked your doctors why they prescribed a particular brand of pill? For a surprisingly large number, the honest answer is that there are a number of pills that all have the same effect, but the one prescribed is made by the company that gives them thousands of dollars in fees and gifts.
Mithun Sridharan, Business Development Manager, Corporate Quality Consulting, 5/10/2013 Comment now
Over the course of this decade, we could expect big data applications to enable truly personalized healthcare solutions, based on an individual's and his or her family's medical history, characteristics, and progression over time.
John Edwards, Technology Journalist & Author, 5/7/2013 Comment now
The largest biotech companies are amassing multiple petabytes of data containing an array of useful drug development resources, such as patient outcomes, gene expression profiles, DNA sequencing data, and biomarker reliability. Putting all of this big data to productive use in the quest to find new treatments and streamline research and development is ...
James M. Connolly, US Correspondent, 5/6/2013 Comment now
The cellphone can be used to tell a spouse to pick up a loaf of bread on the way home, to help teens text nasty gossip, to get that must-have celebrity search through Google, and to limit the spread of malaria and cholera.
James M. Connolly, US Correspondent, 5/2/2013 Comment now
The General Electric announcement that it is investing $105 million in the EMC/VMware initiative known as Pivotal is worth a closer look, perhaps more for the big data implications than the cloud aspects that seemed to draw the most early attention.
There are many apps available to help us with our taxes, but these apps may come with data-collecting features. This has worried some privacy advocates. According to PC Magazine, a lot of these apps are sharing geolocation data, contact information, and other user data with third parties. This data is used for targeted advertisements.
James J. Gillespie, President & CEO, Center for Healthcare Innovation, 4/19/2013 Comment now
As large research-based pharmaceutical companies struggle with patent cliffs, shrinking government reimbursements, and more international competition -- among many other pressures -- there are widespread calls for new economic, finance, and marketing models, including the leveraging of big data.
Istvan Szegedi, IT Technical Architect, Vodafone UK, 4/18/2013 Comment now
Predictive analytics allows companies to reduce risk, supports more attractive customer experience, and instills better decision making. It is used in financial services, insurance, telecommunications, healthcare... you can name the rest of the industries.
At last week's Big Data Show we were lucky enough to speak to Lauren Walker, Sales Leader at IBM Big Data Solutions, who gave us a great message from her real-time analytics talk: Babies, Brains, and Buses.
This case study focused on the big data's ability to help the survival rate of premature babies by combining machine information and human content in real time.
I want to tackle Hadoop, but before we get there, we're going to need to explore MapReduce. MapReduce is a programming model for processing large datasets, and the clue to its function is in its name.
When you want to pull certain information from your datasets, it "maps" out the relevant information for your query.
Then it "reduces" the information down, sorts it based on any rules you've applied, and gives you just the data you were after.
Virginia is a medical researcher looking to carry out research on diabetes patients. For the purposes of her study, she wants to see any geographical concentrations of diabetes patients who are male, between the ages of 40 and 50, and who smoke.
The map in the MapReduce model finds the data sets which fit Virginia's needs.
Then begins the reduce function -- aggregating geographical data of these records and providing an ordered list of cities with the highest population of the defined type. This simple process has allowed Virginia to identify areas of concentration for further study.
MapReduce itself is pretty straightforward, but once we start ramping up the amount and types of data used we will need Hadoop's help -- which is where things get a bit more complex.