Big Data
Big Data
期刊ISSN: 2167-6461
E-ISSN: 2167-647X
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自引率: 0%
SCI期刊JCR分区
SCI期刊JCR分区等级:2区
按学科分区
COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Q3
COMPUTER SCIENCE, THEORY & METHODS
Q2
COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Q3
COMPUTER SCIENCE, THEORY & METHODS
Q3
《新锐期刊分区表》(2026年3月发布)
大类学科
计算机科学
4区
小类学科
计算机:跨学科应用
4区
计算机:理论方法
4区
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综述期刊
最新中科院SCI期刊分区(2025年3月升级版)
大类学科
计算机科学
4区
小类学科
计算机:跨学科应用
4区
计算机:理论方法
4区
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综述期刊
期刊简介
Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government. Big Data coverage includes: Big data industry standards, New technologies being developed specifically for big data, Data acquisition, cleaning, distribution, and best practices, Data protection, privacy, and policy, Business interests from research to product, The changing role of business intelligence, Visualization and design principles of big data infrastructures, Physical interfaces and robotics, Social networking advantages for Facebook, Twitter, Amazon, Google, etc, Opportunities around big data and how companies can harness it to their advantage.
出版信息
出版商
Mary Ann Liebert Inc.
涉及的研究方向
COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
年文章数
15
出版国家或地区
UNITED STATES
是否OA
Cite Score(2025年最新版)
Cite Score SJR SNIP 排名
9.0 0.692 1.33
学科
大类学科:Decision Sciences
小类学科:Information Systems and Management
分区
Q1
学科
大类学科:Decision Sciences
小类学科:Computer Science Applications
分区
Q1
学科
大类学科:Decision Sciences
小类学科:Information Systems
分区
Q1
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