Is Uncertainty In Data Analysis A Big Challenge For Business

Is Uncertainty In Data Analysis A Big Challenge For Business To support ci, fuzzy logic provides an approach for approximate reasoning and modeling of qualitative data for uncertainty challenges in big data analytics [76, 79, 80] using linguistic quantifiers (i.e., fuzzy sets). it represents uncertain real word and user defined concepts and interpretable fuzzy rules that can be used for inference and. The usage of big data and data analysis in business is becoming a common thing recently. unfortunately, uncertainty in data analysis exists in every phase of data collection. we are not good at thinking about uncertainty in data analysis, which we need to be in 2022 when people talk about uncertainty in data analysis, and when they d.

Pdf Uncertainty In Big Data Analytics Survey Opportunities And Lenges in big data analytics, including uncertainty. ey focus mainly on how uncertainty. impacts the performance of learning from big data, wherea s a separate concern lies in. mitigating. It represents uncertain real word and user defined concepts and interpretable fuzzy rules that can be used for inference and decision mak ing. big data analytics also bear challenges due to the existence of noise in data where the data consists of high degrees of uncertainty and outlier artifacts. Ertainty, and the analytics processes that address the uncertainty inherent in big data.big datain may 201. , big data was announced as the next frontier for productivity, innovation, and. However, little work has been done in the field of uncertainty when applied to big data analytics as well as in the artificial intelligence techniques applied to the datasets. this article reviews previous work in big data analytics and presents a discussion of open challenges and future directions for recognizing and mitigating uncertainty in.

Pdf Uncertainty In Big Data Analytics Survey Opportunities And Ertainty, and the analytics processes that address the uncertainty inherent in big data.big datain may 201. , big data was announced as the next frontier for productivity, innovation, and. However, little work has been done in the field of uncertainty when applied to big data analytics as well as in the artificial intelligence techniques applied to the datasets. this article reviews previous work in big data analytics and presents a discussion of open challenges and future directions for recognizing and mitigating uncertainty in. The contributions of this work are as follows. first, we consider uncertainty challenges in each of the 5 v's big data characteristics. second, we review several techniques on big data analytics with impact of uncertainty for each technique, and also review the impact of uncertainty on several big data analytic techniques. 3. research methodology. in an attempt to better understand and provide more detailed insights to the phenomenon of big data and bit data analytics, the authors respond to the special issue call on big data and analytics in technology and organizational resource management (specifically focusing on conducting – a comprehensive state of the art review that presents big data challenges and big.