Sentence examples for data transformation processes from inspiring English sources

Exact(1)

GIS software contain algorithms for translating between formats, for example, raster → vector, vector → raster, point → TIN, although some error may be introduced by these data transformation processes.

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This is possibly because strongly correlated fields will introduce strong correlations in transformed dataset (as we have already explained about the WEKA data transformation process for forecasting [38]).

First, a temporary list newList is created to store migrated data during the data transformation process (Line 1).

A potential source of error in the risk estimate is the data transformation process.

By preserving the history of each commit, we hope to make the data transformation process more transparent, but also make it easier for curators to obtain proper credit for their work.

Furthermore, we exemplify our approach and show how a single declarative description helps to orchestrate a complete tool chain, beginning with the download of datasets, and through to the installation of the datasets for a variety of tool applications, including data and query transformation processes and reasoning services.

Coupling a data mart to a data warehouse through one or more structured and reproducible transformation processes allows data warehouse architects to easily maintain a well defined data source while providing clinical researchers with necessary clinical research data.

It starts with data selection and data preparation through cleansing and transformation processes.

The formal model for the four layers, called data type, data states and transformations, processes and system architecture layers respectively, is based on an integration of abstract data types and structured transition systems.

The service offers a process of data transformation that allows companies to then utilize streaming information in any number of ways.

The interplay makes this process of data transformation more accessible to business data analysts, while increasing the productivity of quantitative data scientists who can use the human-machine interaction to get through various types of data in a faster manner.

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