Mike Loukides is an editor for O'Reilly & Associates. He is the author of System Performance Tuning and UNIX for FORTRAN Programmers. Mike's interests are system administration, networking, programming languages, and computer architecture. His academic background includes degrees in electrical engineering (B.S.) and English literature (Ph.D.).
Disruptive Possibilities provides an historically-informed overview through a wide range of topics, from the evolution of commodity supercomputing and the simplicity of big data technology, to the ways conventional clouds differ from Hadoop analytics clouds. This relentlessly innovative form of computing will soon become standard practice for organizations of any size attempting to derive insight from the tsunami of data engulfing them.
Replacing legacy silos—whether they’re infrastructure, organizational, or vendor silos—with a platform-centric perspective is just one of the big stories of big data. To reap maximum value from the myriad forms of data, organizations and vendors will have to adopt highly collaborative habits and methodologies.
Based on the survey data, the authors found that data scientists today can be clustered into four subgroups, each with a different mix of skillsets. Their purpose is to identify a new, more precise vocabulary for data science roles, teams, and career paths.
This report describes:Four data scientist clusters: Data Businesspeople, Data Creatives, Data Developers, and Data ResearchersCases in miscommunication between data scientists and organizations looking to hireWhy "T-shaped" data scientists have an advantage in breadth and depth of skillsHow organizations can apply the survey results to identify, train, integrate, team up, and promote data scientists