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"Traditional data analysis let you predict the future.
Big Data is driving radical changes in traditional data analysis platforms.
Fig. 6 The comparison between traditional data analysis and big data analysis on wireless sensor network.
It is difficult to process semistructured and unstructured data with traditional data analysis techniques.
Traditional data analysis methods, like Fourier and wavelet-based method, require some predefined basis functions to represent a signal.
The design of traditional data analysis methods typically assumed they will be performed in a single machine, with all the data in memory for the data analysis process.
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Crisp input and output data are fundamentally indispensable in traditional data envelopment analysis (DEA).
Because the scores in the traditional data envelopment analysis (DEA) models censored at unity, when one uses the obtained scores as a dependent variable in the regression one should resort to Tobit estimation.
Since in evaluating by traditional data envelopment analysis (DEA) models many decision making units (DMUs) are classified as efficient, a large number of methods for fully ranking both efficient and inefficient DMUs have been proposed.
17 We used a traditional data envelopment analysis (DEA) model and the DEA/Malmquist model to evaluate the efficiency of health centers.
Traditional metagenomic data analysis includes microbial composition taxonomic analysis, alpha diversity, and beta diversity.
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