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Data presentation architecture weds the science of numbers, data and statistics in discovering valuable information from data and making it usable, relevant and actionable with the arts of data visualization, communications, organizational psychology and change management in order to provide business intelligence solutions with the data scope ...
Big data "size" is a constantly moving target; as of 2012 ranging from a few dozen terabytes to many zettabytes of data. [26] Big data requires a set of techniques and technologies with new forms of integration to reveal insights from data-sets that are diverse, complex, and of a massive scale. [27]
Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis.
Big data mining techniques like Map Reduce help narrow down the search for meaning in vast data. Data visualisation is a data analytics technique, which is used to engage the human brain into finding patterns in data. Recognition and cognition of patterns will also lead to the identification of anomalous patterns.
Cultural analytics refers to the use of computational, visualization, and big data methods for the exploration of contemporary and historical cultures. While digital humanities research has focused on text data, cultural analytics has a particular focus on massive cultural data sets of visual material – both digitized visual artifacts and contemporary visual and interactive media.
The techniques rely heavily on user interaction and the human visual system, and exist in the intersection between visual analytics and big data. It is a branch of data visualization. IVA is a suitable technique for analyzing high-dimensional data that has a large number of data points, where simple graphing and non-interactive techniques give ...
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