Granulate Issues Findings from State of Cloud Computing Survey Highlighting Underutilization of IT Infrastructure

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ACM Issues Computing Competencies for Undergraduate Data Science Curricula

ACM Issues Computing Competencies for Undergraduate Data Science Curricula
Recognizing the explosive growth of data science as a field, as well as the demand for data science training at the undergraduate level, a Data Science Task Force convened by the Association for Computing Machinery’s Education Board recently released “Computing Competencies for Undergraduate Data Science Curricula.” The ACM report seeks to define what the computing/computational contributions are to this new field, as well as to provide guidance on computing-specific competencies in data science for departments offering such programs of study at the undergraduate level. “This seemed like the perfect time for the computing community to define our field’s contributions to a well-rounded data science curriculum,” remarked Paul Leidig, Professor, Grand Valley State University and Co-chair, ACM Data Science Task Force. “Data science is...

Cloud computing: A brief overview of intellectual property issues “in the cloud” | Smart & Biggar

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[co-author: Robert Baker] Cloud computing has increasingly become a dominant model for computer and information technology service, with the majority of businesses worldwide using computing resources and storing data “in the cloud.” However, despite the ease of use and convenience of cloud computing, moving data and services into the cloud raises several legal issues for both cloud computing providers and users. This article highlights some of the issues and questions related to intellectual property (IP) rights raised by cloud computing. What is cloud computing? Generally, “cloud computing" is the remote delivery of computing services and resources to a client. Data is stored and/or processed remotely from the client, on infrastructure that is generally called the “cloud.” The client can access this infrastructure remotely, usually...