BigDataFr recommends: Big Data Analytics Using Cloud and Crowd […]The increasing application of social and human-enabled systems in people’s daily life from one side and from the other side the fast growth of mobile and smart phones technologies have resulted in generating tremendous amount of data, also referred to as big data, and a need […]
Documentation
[Data Science Central] BigDataFr recommends: Industrialising Data Science
BigDataFr recommends: Industrialising Data Science […] If DS is to fulfil its promise, it needs to industrialise. This blog explains what I mean by this, and proposes a number of issues which must be addressed if it is to do so. The application of pattern recognition technology to large datasets has revolutionised the digital economy. […]
[arXiv] BigDataFr recommends: From Big Data To Important Information
BigDataFr recommends: From Big Data To Important Information […]Advances in science are being sought in newly available opportunities to collect massive quantities of data about complex systems. While key advances are being made in detailed mapping of systems, how to relate this data to solving many of the challenges facing humanity is unclear. The questions […]
[Data Science Central] BigDataFr recommends: Citizen Data Scientist – Care, Feeding and Control
BigDataFr recommends: Citizen Data Scientist – Care, Feeding and Control […]Thanks to Gartner the term ‘Citizen Data Scientist’ has become ingrained in our professional literature, in the strategies of analytic platform developers, and even in the strategies of companies committed to advanced analytics. Gartner also recently forecast that the ranks of the Citizen Data Scientist […]
[arXiv] BigDataFr recommends: Crisis Analytics: Big Data Driven Crisis Response
BigDataFr recommends: Crisis Analytics: Big Data Driven Crisis Response […]Disasters have long been a scourge for humanity. With the advances in technology (in terms of computing, communications, and the ability to process and analyze big data), our ability to respond to disasters is at an inflection point. There is great optimism that big data tools […]
[Data Science Central] BigDataFr recommends: 19 Worst Mistakes at Data Science Job Interviews
BigDataFr recommends: 19 Worst Mistakes at Data Science Job Interviews […] This applies to many tech job interviews. But here we provide specific advice for data scientists and other professionals with a similar background. More advice is being added regularly. Here’s the list: 1) Not doing any research on the company prior to the interview. […]
[arXiv] BigDataFr recommends: Market Model and Optimal Pricing Scheme of Big Data and Internet of Things (IoT)
BigDataFr recommends: Market Model and Optimal Pricing Scheme of Big Data and Internet of Things (IoT) […]Big data has been emerging as a new approach in utilizing large datasets to optimize complex system operations. Big data is fueled with Internet-of-Things (IoT) services that generate immense sensory data from numerous sensors and devices. While most current […]
[O’R] BigDataFr recommends: Insightful applications: The next inflection in big data
BigDataFr recommends: Insightful applications: The next inflection in big data […] In previous posts, I wrote about the need for insight generation and provided an example of an insightful application. I maintain that insightful applications are the key to businesses effectively exploiting big data in order to improve decision-making and address important problems. To better […]
[Datasciencecentral] BigDataFr recommends: BIG Data & Analytics, Data Science, Machine Learning – Random Insights!
BigDataFr recommends: BIG Data & Analytics, Data Science, Machine Learning – Random Insights! #1: What really is BIG Data? Today, we can store and process so much data that we have nearly captured reality; no more sampling biases/ errors or related issues – this is my definition of Big Data; not tera or peta bytes! […]
[arXiv] BigDataFr recommends: Streaming Big Data meets Backpressure in Distributed Network Computation
BigDataFr recommends: Streaming Big Data meets Backpressure in Distributed Network Computation […] We study network response to queries that require computation of remotely located data and seek to characterize the performance limits in terms of maximum sustainable query rate that can be satisfied. The available resources include (i) a communication network graph with links over […]