Posts Tagged ‘cloud technologies’

The Skills Gap: How to Close the Gap in Your Career

8466829513_1e25c55942

Greg Satell of Forbes recently wrote, “In the late 90’s McKinsey declared the war for talent and argued that, in a knowledge economy, having the right people is even more important than having the right strategy or technology.  Recruiting and retaining the ‘best and the brightest’ quickly became a corporate mantra. Yet today, the firm is more concerned with the skills gap.  In data science, for example it estimates a shortfall of 140,000 to 190,000 data scientists and 1.5 million managers who have the skills needed to use the insights to drive decisions. But even that understates the problem. With technology accelerating change in the marketplace and automation replacing highly skilled workers with robots, the decision to invest in any particular set of skills is far from a forgone conclusion and platitudes about ‘investing in our people’ will no longer suffice.  We need to start thinking seriously about viable strategies for managing the skills gap.” Read more

NASA Moves to the Cloud

open

Kathleen Hickey of GCN.com reports, “NASA’s OpenNEX is one of the latest federal research projects moving to the cloud to improve collaboration with the academic, public and private sectors. In doing so, the space agency is using Amazon Web Services to make terabytes worth of climate and Earth science data available to researchers, app developers, academia and the public. The first data sets became available in March and include temperature, precipitation and climate change projections, as well as data processing tools fromNASA’s Earth Exchange (NEX), a research and collaboration platform from  NASA’s Advanced Supercomputing Facility at Ames Research Center in California.” Read more

Bringing Together the Cloud & Semantic Tech

Eric Little of Bio-ITWorld recently discussed how private cloud technologies can be used to improve semantic technologies. He writes, “While semantic technologies provide a sophisticated way of modeling complex relationships between data, the graphs that are created within semantic solutions can quickly grow to enormous sizes, given that they capture not only the elements contained within an enterprise’s raw data, but the added litany of related facts and relationships generated by automated reasoning, where 10-100 times as much new data can be generated from a single data source. As an example, imagine taking one’s raw assay data on a given compound, then linking it to all known data about related clinical studies and phenotypic effects, as well as underlying genomics data.” Read more