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Corral represents an improvement over commonly found data processing pipelines in astronomysince the design pattern eases the programmer from dealing with processing flow and parallelization issues, allowing them to focus on the specific algorithms needed for the successive data transformations and at the same time provides a broad measure of quality over the created pipeline.
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Overall compliance was low (930/1761; 52.8%) and decreased with each successive data collection phase.
The blocks are a time series of successive data.
Data transformations are conducted in R.2.15.0 [ 31].
We did not do any data transformations.
Data transformation 3.
Data ingestion with data transformation and without data transformation.
(a) Before data transformation and (b) after log data transformation.
Intermediate data transformation using a MapReduce job.
Clustering is another utilized data transformation method.
Implement the data transformation logic within the data pipeline.
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