"complex data analysis" is a correct and usable phrase in written English.
It refers to the process of analyzing large and intricate sets of data to extract meaningful insights and patterns. Example: "The team of researchers conducted a complex data analysis to uncover the underlying factors behind the sudden decline in sales figures."
He adds that she's good at digging through complex data analysis and getting to the core issues.
However, this technique is difficult to apply for general measurements due to its need for arduous sample preparation and its complex data analysis.
Complex data analysis is already a challenge to traditional flow cytometry software.
Talk or presentation, 16, February, 2011; Presented at the Ninth Biennial Ptolemy Miniconference, Berkeley, CA. Scientific workflows often aim at fully automating complex data analysis pipelines.
However, the conducted experimental tests lead to huge amount of heterogeneous data and thus require a complex data analysis process.
Furthermore, A user can access the data structure both from a GUI and a script, enabling relatively complex data analysis workflow built quickly on πScope.
In addition, the ability to start, pause, restart/continue and stop the workflow execution enables the construction, validation, debugging and on-the-fly modification of complex data-analysis workflows.
The necessary efficient and fast processing of these high-throughput datasets requires the integration of a large number of bio/immunoinformatics tools into complex data-analysis pipelines.
Since the LCLS facility started operating in 2009, it has accumulated many petabytes of complex data for analysis, and the timely processing of this data has proven to be a challenge for the community.
Although randomized experiments can be expensive and complex, the data analysis involved brings the process full circle, and often pays for itself in terms of the return on investment.
"Machine learning" — an AI buzzword that describes a form of ultra-fast, complex computer data analysis and statistical modeling — was repeated throughout the 2½-hour presentation, delivered to an audience of roughly 6,000 developers here.
