Examples of using Large data sets in English and their translations into Swedish
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Computer
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especially when working with large data sets.
Support for large data sets Excel 2010 handles workbooks that contain massive amounts of data more efficiently.
even archiving large data sets spanning multiple discs is possible thanks to disc spanning.
FileCatalyst uses a patent-pending UDP-based protocol that is faster in transferring large data sets when there is high latency
proved proficient in processing and analyzing large data sets, said Robert Lundmark.
Explore and understand the entire design space using modern simulation results analytics to process large data sets.
making it easier to navigate large data sets.
information analytics with a focus on analyzing large data sets, so-called Big Data. .
Nonetheless, the researchers try to account for such factors by applying advanced statistical methods to analyse the large data sets," he explains.
such as identifying subtle anomalies in large data sets.
Big Data is a term that refers to solutions destined for storing and processing large data sets.
Increase competence and capacity within the analysis and management of large data sets, as well as artificial intelligence, to generate clinically relevant hypotheses
Visualise very large data sets directly from a wide variety of cloud sources like Azure SQL Database
With Power Pivot you can work with large data sets, build extensive relationships,
Accessing large data sets with Direct Discovery Direct Discovery expands the associative capabilities of the Qlik Sense in-memory data model by providing access to additional source data through an aggregated query that seamlessly associates larger data sets with in-memory data. .
which is a method to visualize large data sets and thus find the most important information.
Visualise very large data sets directly from a wide variety of cloud sources, such as Azure SQL Database
Visualize very large data sets directly from a wide variety of cloud sources like Azure SQL Database,
It takes less time to perform activities commonly performed on large data sets, such as filtering and sorting the data,
A paramount challenge in analyzing the large data sets is in the distinction of true protein interactions from the experimental noise that exists in the raw data obtained by a large-scale screening method.