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Preface

Preface Ann. Data. Sci. (2015) 2(1):1–3 DOI 10.1007/s40745-015-0036-x Some Advanced Techniques in Data Science 1,2,3 1,2 Yong Shi · Yingjie Tian Published online: 26 May 2015 © Springer-Verlag Berlin Heidelberg 2015 This issue of 2015, Annals of Data Science (Volume 2, No. 1) presents seven papers from the several areas of data science. They are contributed from 20 authors and the co-authors come from six countries and regions: Australia, Brazil, Iran, Spain, Russia and UK. The first paper, “Forecasting with Big Data: A Review,” by Hossein Hassani1 and Emmanuel Sirimal Silva, presents a comprehensive review on the use of Big Data for forecasting by identifying and reviewing the problems, potential, challenges and most importantly the related applications. Skills, hardware and software, algorithm architecture, statistical significance, the signal to noise ratio and the nature of Big Data itself are identified as the major challenges which are hindering the process of obtaining meaningful forecasts from Big Data. The review finds that at present, the fields of economics, energy and population dynamics have been the major exploiters of Big Data forecasting whilst factor models, Bayesian models and neural networks are the most common tools adopted for forecasting with Big Data. The second paper, http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Data Science Springer Journals

Preface

Shi, Yong; Tian, Yingjie
Annals of Data Science , Volume 2 (1) – May 26, 2015
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Publisher
Springer Journals
Copyright
Copyright © 2015 by Springer-Verlag Berlin Heidelberg
Subject
Economics / Management Science; Business/Management Science, general; Statistics for Business/Economics/Mathematical Finance/Insurance; Computing Methodologies
ISSN
2198-5804
eISSN
2198-5812
DOI
10.1007/s40745-015-0036-x
Publisher site
See Article on Publisher Site

Abstract

Ann. Data. Sci. (2015) 2(1):1–3 DOI 10.1007/s40745-015-0036-x Some Advanced Techniques in Data Science 1,2,3 1,2 Yong Shi · Yingjie Tian Published online: 26 May 2015 © Springer-Verlag Berlin Heidelberg 2015 This issue of 2015, Annals of Data Science (Volume 2, No. 1) presents seven papers from the several areas of data science. They are contributed from 20 authors and the co-authors come from six countries and regions: Australia, Brazil, Iran, Spain, Russia and UK. The first paper, “Forecasting with Big Data: A Review,” by Hossein Hassani1 and Emmanuel Sirimal Silva, presents a comprehensive review on the use of Big Data for forecasting by identifying and reviewing the problems, potential, challenges and most importantly the related applications. Skills, hardware and software, algorithm architecture, statistical significance, the signal to noise ratio and the nature of Big Data itself are identified as the major challenges which are hindering the process of obtaining meaningful forecasts from Big Data. The review finds that at present, the fields of economics, energy and population dynamics have been the major exploiters of Big Data forecasting whilst factor models, Bayesian models and neural networks are the most common tools adopted for forecasting with Big Data. The second paper,

Journal

Annals of Data Science – Springer Journals

Published: May 26, 2015

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