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Making data visualization more efficient and effective: a survey
by
Qin, Xuedi
, Luo, Yuyu
, Tang, Nan
, Li, Guoliang
in
Big Data
/ Data analysis
/ Data processing
/ Data visualization
/ Language
/ Power
/ Scientific visualization
/ Specifications
/ Visualization
2020
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Do you wish to request the book?
Making data visualization more efficient and effective: a survey
by
Qin, Xuedi
, Luo, Yuyu
, Tang, Nan
, Li, Guoliang
in
Big Data
/ Data analysis
/ Data processing
/ Data visualization
/ Language
/ Power
/ Scientific visualization
/ Specifications
/ Visualization
2020
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Making data visualization more efficient and effective: a survey
Journal Article
Making data visualization more efficient and effective: a survey
2020
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Overview
Data visualization is crucial in today’s data-driven business world, which has been widely used for helping decision making that is closely related to major revenues of many industrial companies. However, due to the high demand of data processing w.r.t. the volume, velocity, and veracity of data, there is an emerging need for database experts to help for efficient and effective data visualization. In response to this demand, this article surveys techniques that make data visualization more efficient and effective. (1) Visualization specifications define how the users can specify their requirements for generating visualizations. (2) Efficient approaches for data visualization process the data and a given visualization specification, which then produce visualizations with the primary target to be efficient and scalable at an interactive speed. (3) Data visualization recommendation is to auto-complete an incomplete specification, or to discover more interesting visualizations based on a reference visualization.
Publisher
Springer Nature B.V
Subject
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