This paper focuses on four aspects: 1) introduces data processing methods including data cleaning, data integration, and dimension reduction and data normalization for heterogeneous data and Big Data analytics; 2) presents big data concepts, Big Data analytics, and Big Data tools; 3) compares tradi...
On the other hands, popular Big Data platforms such as MapReduce and Apache Spark address big data challenges with data and computation distribution and in-memory caching. However, these CPU-only frameworks still struggle to meet the increasing analytics speed requirements. Besides, because of the ...
Heterogeneous data and big data analytics. Autom Control Inf Sci. 2017;3:8–15.10.12691/acis-3-1-3Search in Google Scholar [13] Lau BPL, Marakkalage SH, Zhou Y, Hassan NU, Yuen C, Zhang M, et al. A survey of data fusion in smart city applications. Inf Fusion. 2019;52(2019):...
Companies are designing computing systems to take in data from multiple regions and units. This is enabling them to become truly global when looking at AI and Big Data. There are limited restrictions on how companies are viewing information and can gain access to rich insights at any time. Thi...
Data science is a powerful field for gaining insights, comparing, and predicting behaviors from datasets. However, the diversity of methods and hypotheses needed to abstract a dataset exhibits a lack of genericity. Moreover, the shape of a dataset, which
Big Data and Analytics HPC Optane About the Author Patricia (Trish) A. Damkroger is vice president and general manager of the High Performance Computing organization in the Data Platforms Group at Intel Corporation. She leads Intel’s global technical and high-performance comput...
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Big data analytics on location-based social networks for knowledge generation in tourism - the case of Crete island Despite the massive volumes of data tourists generate during their visit to a destination, there is little knowledge of their spatial activity and percepti... I Kopanakis,J Makridis...
Every industry has signicant data output as a product of their working process, and with the recent advent of big data mining and integrated data warehousing it is the case for a robust methodology for assessing the quality for sustainable and consistent processing. In this paper a review is ...
aWhile care must betaken when developing these insights to ensure that privacy is not violated,future maturity models may benefit from “big data” collection and analytics approaches. 当关心必需betaken时,当开发这些洞察保证保密性没有被违犯,未来成熟模型也许受益于“大数据”汇集和analytics方法。 [...