The phrase "a data preparation" is not correct in standard English usage.
It should be "data preparation" without the article "a," as "data preparation" is typically used as an uncountable noun.
Example: "Data preparation is a crucial step in the data analysis process."
Alternatives: "data processing" or "data cleansing."
In the data mining context, the separation of the last sequence of approximation coefficients can be regarded as a data preparation operation.
A data preparation stage of the process starts from defining the time units and partitioning an audit trail over time units.
In this paper, we report on our experience in using a web-scale platform (i.e., Pig) as a data preparation language to aid large-scale MSR studies.
The main three steps of this workflow are (a) data preparation and modification; (b) data process and workflow; and (c) user interface and data access as detailed in Sects.
In the following we present CVIIM, our new measure for the extent of bias induced by incomplete CV with respect to a data preparation step of interest.
The selection of features which exhibit high variability across the observations is another example of a data preparation step often performed when analyzing microarray data.
ElPrep is a tool that combines all data preparation steps and outputs a SAM file that conforms to the GATK requirements.
Data analytics platform Tableau today announced the launch of both a new data preparation product and a new subscription pricing plan.
This measure can be used to determine whether a specific data preparation step should, as a general rule, be performed in each CV iteration or whether an incomplete CV procedure would be acceptable in practice.
However, the level of data detail required for this model also provides a drawback: data preparation, meta-analysis, and verification for a new series of analysis are non-trivial.
For the prediction of external data, such a separate data preparation procedure may be suitable in some situations, for example when the external data behaves very differently from the training data: by a separate processing the data preparation procedure can adjust itself to the peculiarities of the external data; see e.g. [ 16].
